system

Abstract

Provide a system. A method for a user to input individual profile information and learning goals; A means for generating a learning curriculum based on the user information received by the server; means for transmitting the generated learning curriculum to a user's terminal and displaying it; A means for users to input questions that arise during learning, and for the server to instantly generate answers using AI; a means for the server to schedule online sessions with experts and teachers in real time; means for transmitting user learning progress data from the terminal to a server, and for the server to generate a progress report; A system including:

Description

[Technical Field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Traditional education systems have been unable to flexibly respond to the diverse needs of learners, and have been limited to providing uniform curricula and fixed content. Furthermore, a lack of feedback and appropriate support based on individual learning progress makes it difficult to achieve efficient learning. Furthermore, it is difficult to obtain timely, expert answers to questions or concerns that arise during learning, which leads to a decline in learner motivation and a decline in learning efficiency. [Means for solving the problem]

[0005] The present invention provides a system in which a user inputs individual profile information and learning goals, and a server generates a learning curriculum based on the received user information, thereby enabling the provision of an individually customized learning program for each learner. The system also includes a means for transmitting and displaying the generated learning curriculum to the user's terminal, facilitating the process of starting learning. Furthermore, the system provides real-time learning support by allowing the user to input questions that arise during learning, and the server instantly generates answers using AI. In addition, the server provides a means for scheduling online sessions with experts and teachers in real time, providing an environment in which each learner can receive specialized and personalized instruction. Furthermore, the system includes a means for transmitting the user's learning progress data from the terminal to the server, which then generates a progress report, enabling effective analysis and feedback of learning and supporting an efficient learning process.

[0006] "User" refers to an individual who uses this system to study.

[0007] "Profile Information" refers to data containing basic information about a User and their learning interests and goals.

[0008] "Server" refers to a computer system that receives user information and provides data processing and AI functions.

[0009] "Learning Curriculum" refers to a specific learning plan created based on a user's profile information and learning goals.

[0010] "Terminal" refers to a device that allows a user to access the system, view the learning curriculum, and input questions.

[0011] "AI" refers to a program that uses artificial intelligence technology to generate answers to user questions.

[0012] "Online session" refers to an interactive means of communication that allows users to interact with experts or teachers in real time.

[0013] "Progress data" refers to information that indicates the progress of a user's learning activity.

[0014] "Progress Report" refers to a report that is generated by analyzing progress data and includes learning assessments and feedback. [Brief explanation of the drawings]

[0015] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0016] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0019] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0020] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0021] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0023] [First embodiment]

[0024] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0025] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0026] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0028] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0031] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0033] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0035] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0036] This invention relates to an educational platform that utilizes AI interactive chatbots, and describes specific implementation methods for the system to provide individually customized learning experiences.

[0037] System configuration

[0038] This system consists of three components: the user, the device, and the server, and these components work together to realize education. It also integrates AI chatbots with support from experts and teachers.

[0039] User Registration and Authentication

[0040] 1. The user accesses the educational platform's website or app and enters profile information such as name, email address, and password on the new registration screen.

[0041] 2. The terminal sends the entered information to the server.

[0042] 3. The server uses this information to record the user information in its database and sends the user an email containing an authentication link.

[0043] 4. When the user clicks on the link in the verification email, the account is activated on the server side.

[0044] Customized educational content

[0045] 1. After logging in, users enter their interests and learning goals into the profile settings page.

[0046] 2. The terminal sends this input information to the server.

[0047] 3. Based on the received information, the server uses an AI chatbot to generate an individually customized learning curriculum.

[0048] 4. The server sends the generated curriculum to the terminal, where it is displayed to the user.

[0049] Interactive learning support

[0050] 1. When a user has a question or concern that arises during their study, they send the question to the server via their terminal.

[0051] 2. The server analyzes the received question using an AI chatbot and instantly generates an answer.

[0052] 3. The server sends the generated answer to the device, providing the user with a real-time answer, and may redirect the question to an expert if necessary.

[0053] Real-time support and feedback

[0054] 1. The server schedules online sessions with experts and teachers based on the user's learning progress, etc.

[0055] 2. The device displays a notification of the online session to the user and provides the session link at the specified time.

[0056] 3. When the designated session time arrives, the user clicks on the notification link to begin a real-time conversation with the expert or teacher.

[0057] Progress management and evaluation

[0058] 1. The device periodically sends the user's learning progress data (e.g., completed assignments, test results, study time) to the server.

[0059] 2. The server records the received progress data in a database and analyzes it.

[0060] 3. The server generates a progress report based on the analysis results and sends it to the device.

[0061] 4. The device displays a progress report to the user, who can use the report to plan their next learning steps.

[0062] Specific Examples

[0063] For example, let's say a junior high school student, Mr. A, wants to study mathematics efficiently. In this case, the system works as follows:

[0064] 1. A user (Mr. A) registers and logs in after completing email authentication.

[0065] 2. User (A) selects "High School Mathematics" in the profile settings and enters his / her learning goals.

[0066] 3. The server generates a high school mathematics curriculum based on this information and displays it on the terminal.

[0067] 4. While studying, a user (Mr. A) types a question: "Please teach me the basics of differential and integral calculus."

[0068] 5. The server uses an AI chatbot to instantly generate a response and display it on the device.

[0069] 6. The server schedules an online session with an expert, and the user (Person A) joins the session and asks questions directly.

[0070] 7. The device sends Mr. A's learning progress data to the server, and the server generates a progress report and sends it to the device.

[0071] 8. User (A) reviews the report and plans the next learning steps.

[0072] In this way, the system provides an individually customized learning experience, enabling efficient and effective learning with the support of experts.

[0073] The processing flow will be explained below.

[0074] Program processing steps

[0075] User Registration and Authentication

[0076] Step 1:

[0077] A user accesses the education platform's website or app and enters profile information such as name, email address, and password on the new registration screen.

[0078] Step 2:

[0079] The device transmits the entered profile information to the server.

[0080] Step 3:

[0081] The server stores user information in a database based on the received profile information.

[0082] Step 4:

[0083] The server sends an email containing a verification link to the user's email address.

[0084] Step 5:

[0085] The user clicks the link in the verification email to activate their account.

[0086] Step 6:

[0087] The server verifies that the user clicked the link and updates the account status to "active."

[0088] Customized educational content

[0089] Step 1:

[0090] User logs in and visits the profile settings page.

[0091] Step 2:

[0092] The user inputs their area of ​​interest or learning goal (e.g., mathematics, high school level, specifically calculus).

[0093] Step 3:

[0094] The terminal transmits the user's input information to the server.

[0095] Step 4:

[0096] Based on the information received by the server, the AI ​​chatbot's algorithm is run to generate a customized learning curriculum.

[0097] Step 5:

[0098] The server transmits the generated curriculum to the terminal.

[0099] Step 6:

[0100] The terminal displays the curriculum to the user and provides a button to start learning.

[0101] Interactive learning support

[0102] Step 1:

[0103] The user inputs questions or doubts that arise during the study (e.g., "Please teach me the basics of calculus").

[0104] Step 2:

[0105] The terminal sends the user's question to the server.

[0106] Step 3:

[0107] The server analyzes the questions it receives and has the AI ​​chatbot generate answers.

[0108] Step 4:

[0109] The server sends the answer obtained from the AI ​​chatbot to the terminal.

[0110] Step 5:

[0111] The device displays the answers to the user and also provides a field where they can enter additional questions if desired.

[0112] Real-time support and feedback

[0113] Step 1:

[0114] The server schedules online sessions with experts and teachers (based on the user's learning progress and schedule).

[0115] Step 2:

[0116] The server sends a notification to the device containing the session date and time and a link.

[0117] Step 3:

[0118] The terminal displays a notification of the online session to the user.

[0119] Step 4:

[0120] The user clicks the session link from the notification at the specified time.

[0121] Step 5:

[0122] The server initiates the online session, and the expert or teacher connects.

[0123] Step 6:

[0124] Users can ask questions directly during the session and receive real-time feedback.

[0125] Progress management and evaluation

[0126] Step 1:

[0127] The device periodically sends the user's learning progress data (completed assignments, test results, time elapsed, etc.) to the server.

[0128] Step 2:

[0129] The server records the received progress data in a database.

[0130] Step 3:

[0131] The server analyzes the progress data and evaluates trends and rate of progress.

[0132] Step 4:

[0133] The server generates a progress report based on the user's learning status.

[0134] Step 5:

[0135] The server generates a progress report and sends it to the device.

[0136] Step 6:

[0137] The device displays progress reports to the user and suggests next learning steps.

[0138] Example 1

[0139] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0140] Traditional educational platforms lack the ability to customize content to meet individual learning needs and goals, making it difficult for users to learn efficiently and effectively. Furthermore, the mechanisms for providing real-time support from experts and teachers are incomplete, limiting the means by which users can get immediate answers to questions that arise during their studies. Progress management and assessment must also be done manually, placing a burden on users.

[0141] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0142] In this invention, the server includes: means for a user to input individual profile information and learning goals; means for the terminal to encrypt the input information and transmit it to the server; means for generating an individually customized learning curriculum based on the user information received by the server; means for transmitting the generated learning curriculum to the user's terminal and displaying it; means for the user to input questions that arise during learning and for the terminal to transmit the questions to the server; means for the server to instantly generate answers to the questions received by the server using an AI model; means for the server to schedule online sessions with experts or teachers in real time; means for the terminal to display notifications of the online sessions to the user; means for the terminal to transmit the user's learning progress data to the server; means for the server to analyze the received learning progress data and generate a progress report; and means for the terminal to transmit the generated progress report to the terminal and display it to the user. This provides a customized learning experience that meets the user's individual learning needs, enables real-time question resolution and direct communication with experts, and automates progress management and evaluation, thereby enabling efficient and effective learning for the user.

[0143] "User" refers to an individual who uses the educational platform and who enters individual profile information and learning goals.

[0144] "Terminal" refers to a device such as a PC or smartphone, which is a means for sending information from the user to the server and receiving and displaying information from the server.

[0145] The "server" is a computer system that controls the entire system, including generating a learning curriculum based on received user information, answering user questions, and analyzing progress data.

[0146] "Profile Information" means personal identification information such as name, email address, and password that a User enters when registering on the Education Platform.

[0147] "Learning goals" refer to the specific learning outcomes or objectives that a user wishes to achieve, and serve as the basis for the system to generate a customized learning curriculum.

[0148] "Learning curriculum" refers to an individual learning schedule and learning content generated based on a user's profile information and learning goals.

[0149] A "question" is something that a user inputs when they are unsure about something they are unsure about while studying, and is something that requires an answer.

[0150] An "AI model" refers to an algorithm or system that uses artificial intelligence technology to analyze data and generate answers to user questions.

[0151] An "expert" refers to an individual or occupation that has advanced knowledge and experience in a specific field of study and provides expert answers to users' questions and inquiries.

[0152] "Online Session" refers to an opportunity for interaction and instruction with an expert or teacher conducted in real time via the Internet.

[0153] "Notifications" means information sent by the System to Users, including schedules for online sessions and important updates.

[0154] "Study progress data" is data that indicates how far a user has progressed in their studies, and includes information such as completed assignments, test results, and study time.

[0155] A "progress report" is a report summarizing the results of an analysis of a user's learning progress data, and serves as reference material when the user makes future learning plans.

[0156] This invention relates to an educational platform that utilizes AI interactive chatbots, and describes specific implementation methods for the system to provide individually customized learning experiences.

[0157] System configuration

[0158] This system consists of three entities: the user, the terminal, and the server. The specific roles and operations of each entity are explained below.

[0159] User Registration and Authentication

[0160] A user accesses the education platform's website or app and enters profile information such as name, email address, and password on the new registration screen. The device encrypts the entered information and sends it to the server via HTTPS. The server decrypts the received user information and stores it in a back-end SQL database (e.g., MySQL (registered trademark) or PostgreSQL). The server then sends an email containing an authentication link to the user's email address. This authentication is performed using an email sending system such as SendGrid or Amazon SES. When the user clicks the link in the authentication email, the server verifies the token in the authentication link and updates the database to activate the account.

[0161] Customized educational content

[0162] After logging in, users enter their interests and learning goals on a profile setting page. The device encrypts this input information and sends it to the server. The server then sends the received user information to an AI model (e.g., OpenAI's GPT-4) to generate an individually customized learning curriculum. This curriculum is sent to the device in JSON format, and the device displays it to the user.

[0163] Interactive learning support

[0164] When a user inputs a question or concern that arises during learning, the device sends the question to the server. The server sends the question to the AI ​​chatbot (generative AI model), which analyzes it in real time and generates an answer. The server then sends the generated answer to the device, which displays it to the user.

[0165] Example prompt sentence:

[0166] User: Teach me the basics of calculus.

[0167] AI Chatbot: Calculus is an important subject in high school mathematics. First of all, differentiation is the operation of finding the rate of change of a function. For example, the derivative of y = x^2 is dy / dx = 2x. On the other hand, integration is the operation of finding the cumulative amount of a function, and the integral of y = x^2 is ∫x^2 dx = (1 / 3)x^3 + C. Please let me know if there are any specific topics or problems you would like to know about.

[0168] Real-time support and feedback

[0169] The server schedules online sessions with experts or teachers based on the user's learning progress. The device displays a notification of the online session to the user and presents a session link at the specified time. The user clicks the link at the specified session time to interact with the expert or teacher in real time.

[0170] Progress management and evaluation

[0171] The device periodically sends the user's learning progress data (e.g., completed assignments, test results, and study time) to the server. The server records the received progress data in a database and performs data analysis. This analysis can be performed using Python tools such as Pandas or NumPy. The server generates a progress report based on the analysis results and sends it to the device. The device displays the progress report to the user, who can use it to plan their next learning steps.

[0172] Specific examples

[0173] For example, consider the case where a junior high school student, Person A, is working on a new mathematics topic, "Calculus." The user (Person A) registers and logs in after email authentication. Person A enters that he or she is interested in "Calculus" in his or her profile settings, and the server uses this information to generate an individually customized curriculum, which is sent to the device and displayed. If Person A enters a question while studying, such as "Teach me the basics of calculus," the server uses an AI model to instantly generate an answer and displays it on the device. The server also schedules an online session with an expert, with Person A interacting in real time at the specified time. The device sends Person A's learning progress data to the server, which generates a progress report and sends it to the device, where Person A can review the report and plan his or her next learning steps.

[0174] In this way, this system allows users to customize their learning experience and receive real-time expert support, making learning efficient and effective.

[0175] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0176] Step 1:

[0177] Users access the educational platform's website or app and enter profile information such as their name, email address, and password on the new registration screen.

[0178] Input: User profile information such as name, email address, and password.

[0179] Output: Encrypted user information.

[0180] What happens: A user fills out a form using a browser or app and clicks the "Register" button.

[0181] Step 2:

[0182] The terminal encrypts the entered information and sends it to the server via the HTTPS protocol.

[0183] Input: Profile information entered by the user.

[0184] Output: Encrypted user information sent to the server.

[0185] Specific operation: The terminal encrypts input data using SSL / TLS and sends an HTTPS request to the server.

[0186] Step 3:

[0187] The server decrypts the received user information and stores it in a back-end SQL database (e.g. MySQL or PostgreSQL).

[0188] Input: Encrypted user information.

[0189] Output: User information stored in the database.

[0190] Specific operation: The server decrypts the received data using SSL / TLS and inserts the user information into the database using an SQL query.

[0191] Step 4:

[0192] The server sends an email containing an authentication link to the user's email address. For example, SendGrid or Amazon SES is used as the email sending system.

[0193] Input: The user's email address.

[0194] Output: The authentication email sent to the user.

[0195] Specific operation: The server uses the email API to generate email content and send an authentication link to the specified email address.

[0196] Step 5:

[0197] The user checks their mailbox and clicks on the link in the verification email.

[0198] Input: The link in the verification email.

[0199] Output: The authentication request sent to the server.

[0200] What happens: The user opens the email and clicks on a link, causing the browser to send a request to the server.

[0201] Step 6:

[0202] The server validates the token in the authentication link and updates its database to validate the user account.

[0203] Input: Token for authentication link.

[0204] Output: Activated user account information.

[0205] What happens: The server validates the link's token and updates the user record in the database using an SQL query.

[0206] Step 7:

[0207] After logging in, users enter their interests and learning goals on the profile settings page.

[0208] Input: Information such as interests and learning goals.

[0209] Output: Encrypted learning objective information.

[0210] Specific behavior: A user logs in, enters information on a settings page, and clicks the save button.

[0211] Step 8:

[0212] The terminal encrypts this input information and sends it to the server.

[0213] Input: User-entered interest and learning goal information.

[0214] Output: Encrypted learning objective information sent to the server.

[0215] Specific operation: The terminal encrypts input data using SSL / TLS and sends an HTTPS request to the server.

[0216] Step 9:

[0217] The server sends the received user information to an AI model (e.g., OpenAI's GPT-4) to generate an individually customized learning curriculum.

[0218] Input: User's learning goals, profile information.

[0219] Output: The generated learning curriculum.

[0220] Specific operation: The server sends user information to the AI ​​model and generates a curriculum from the model's response.

[0221] Step 10:

[0222] The server sends the generated curriculum in JSON format to the terminal, which displays it to the user.

[0223] Input: The generated learning curriculum.

[0224] Output: The curriculum that is displayed to the user.

[0225] Specific operation: The server sends curriculum data in JSON format to the terminal, which parses it and displays it on the user interface.

[0226] Step 11:

[0227] When the user inputs any doubts or questions that arise during the study, the terminal sends this question to the server.

[0228] Input: User's doubt or question.

[0229] Output: The query data sent to the server.

[0230] Specific operation: The user enters a question and clicks the send button, causing the device to send the data to the server.

[0231] Step 12:

[0232] The server sends the question to the AI ​​model, which analyzes it and generates an answer in real time.

[0233] Input: The user's question.

[0234] Output: The generated answer.

[0235] How it works: The server passes a question to the AI ​​model and receives the answer generated by the model.

[0236] Step 13:

[0237] The server generates a response and sends it to the terminal, which displays it to the user.

[0238] Input: The generated answer.

[0239] Output: The answer that is displayed to the user.

[0240] Specific operation: The server sends the response data to the terminal, which parses it and displays it on the user interface.

[0241] Step 14:

[0242] The server schedules online sessions with experts and teachers based on the user's learning progress.

[0243] Input: User's learning progress data.

[0244] Output: Online session schedule.

[0245] Specific behavior: The server analyzes the progress data and reserves an online session at the appropriate time.

[0246] Step 15:

[0247] The terminal displays a notification of the online session to the user and presents the session link at the specified time.

[0248] Enter: Schedule an online session.

[0249] Output: The notification and session link that is displayed to the user.

[0250] Specific operation: The terminal receives the session schedule and displays a notification and link on the user interface.

[0251] Step 16:

[0252] Users click on the link at the designated session time to interact with the expert or teacher in real time.

[0253] Input: Online session link.

[0254] Output: Communication with experts and teachers.

[0255] What happens: The user clicks on a link and connects with an expert or teacher via a video conferencing platform or similar.

[0256] Step 17:

[0257] The terminal periodically transmits the user's learning progress data to the server.

[0258] Input: Learning progress data (e.g. completed assignments, test results, study time).

[0259] Output: Progress data sent to the server.

[0260] Specific operation: The device collects progress data at regular intervals, encrypts it, and sends it to the server.

[0261] Step 18:

[0262] The server records the received progress data in a database and performs data analysis.

[0263] Input: Progress data.

[0264] Output: Parsed data.

[0265] Specific operation: The server stores progress data in an SQL database and analyzes it using data analysis tools (e.g., Python's Pandas or NumPy).

[0266] Step 19:

[0267] The server generates a progress report based on the analysis results and sends it to the terminal.

[0268] Input: Analysis results.

[0269] Output: The generated progress report.

[0270] Specific operation: The server aggregates the analysis results, generates a progress report including text and graphs, and sends it to the device in JSON format.

[0271] Step 20:

[0272] The device displays a progress report to the user, who can use it to plan their next learning steps.

[0273] Input: Progress report.

[0274] Output: The report that is displayed to the user.

[0275] Specific operation: The device parses the received report data and displays it visually in the user interface. The user can then check the content and set their next learning goal or plan.

[0276] (Application example 1)

[0277] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0278] Traditional education platforms lack the flexibility to accommodate individual learning requirements. Furthermore, in-factory training lacks a way to accept questions in real time and provide immediate answers. Furthermore, the lack of an environment for direct interaction with experts and instructors during training often results in insufficient learning outcomes. This makes it particularly difficult to provide efficient training in a real-world work environment for new and existing employees.

[0279] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0280] In this invention, the server includes: means for a user to input individual profile information and learning goals; means for generating a learning curriculum based on the user information received by the server; means for transmitting the generated learning curriculum to the user's terminal and displaying it; means for the user to input questions that arise during learning and for the server to instantly generate answers using AI; means for the server to schedule online sessions with experts or instructors in real time; means for transmitting the user's learning progress data from the terminal to the server and for the server to generate progress reports; means for a robot incorporating AI functions to support the user's training and provide on-site work procedures; means for inputting training status and questions to the robot in real time using the terminal and for the robot to instantly respond; and means including a sensor for detecting the user's actions when operating equipment and providing feedback at appropriate times. This allows users to receive individually customized learning experiences, enabling efficient and effective learning through real-time question and answer sessions and dialogue with experts.

[0281] "User" refers to the entity that uses the educational platform, who sets individual learning goals and manages their learning progress.

[0282] "Profile information" refers collectively to personal identification information and study-related information entered by a user.

[0283] "Learning goal" refers to the learning objective or goal that a user wants to achieve.

[0284] "Device" refers to the device (e.g., smartphone, tablet, or computer) used by a User to access the Education Platform.

[0285] "Server" refers to the central processing unit that receives, processes and manages information from users.

[0286] "Learning Curriculum" refers to a set of learning content and plans generated based on a user's profile information and learning goals.

[0287] "AI" refers to artificial intelligence technology, which has the ability to analyze and generate information interactively.

[0288] "Real-time" refers to instantaneous processing and response.

[0289] An "expert" is an individual who has advanced knowledge or skills in a particular field.

[0290] "Instructor" refers to an individual whose role is to provide education and training to users.

[0291] "Online Session" means an interactive educational or training session conducted via the Internet.

[0292] "Progress Data" refers to data and information that indicates a user's learning or training progress.

[0293] "Progress Report" refers to a report summarizing and analyzing a user's learning progress.

[0294] A "robot" is an automated mechanical device that incorporates AI to support user training and learning.

[0295] A "work procedure" refers to a series of steps or methods for accomplishing a particular task.

[0296] A "sensor" refers to a device that detects physical variables (e.g., movement or position) and acquires them as data.

[0297] This invention is an educational platform system using robots with built-in AI functions, which provides individually customized learning experiences and streamlines training within factories. The system mainly consists of a server, terminals, and users. The details are explained below.

[0298] User Registration and Authentication

[0299] A user accesses the educational platform's website or app and enters profile information such as name, email address, and password on the new registration screen. The device sends the entered information to the server, which records it in a database. An email containing a verification link is sent to the user, and when the user clicks the link in the verification email, the account is activated.

[0300] Customized educational content

[0301] After logging in, users enter their interests and learning goals on a profile setting page. The device sends this information to the server, which then uses an AI model to generate an individually customized learning curriculum based on the received information. The generated curriculum is then sent to the device and displayed to the user.

[0302] Interactive learning support

[0303] When a user inputs a question or concern that arises during learning, the question is sent to the server via the device. The server uses an AI chatbot to instantly generate an answer and provides it to the user via the device in real time. If necessary, the question may be redirected to an expert.

[0304] Real-time support and feedback

[0305] The server schedules online sessions with experts or instructors based on the user's learning progress, etc. The device displays a notification of the online session to the user and presents a session link at the specified time. When the specified session time arrives, the user clicks the notification link to begin a real-time dialogue with the expert or instructor.

[0306] Progress management and evaluation

[0307] The device periodically sends the user's learning progress data (e.g., completed assignments, test results, study time) to the server. The server records the received progress data in a database and analyzes it. The server generates a progress report based on the analysis results and sends it to the device to display to the user. The user can use the report to plan their next learning steps.

[0308] Robotic training support

[0309] The robot, which incorporates AI functions, supports user training and provides guidance on on-site work procedures. Training status and questions are input to the robot in real time using a terminal, and the robot responds immediately. In addition, when the user operates equipment, the robot detects the user's movements using built-in sensors and provides feedback at the appropriate time.

[0310] Specific examples

[0311] For example, if a new employee needs to learn how to operate a new machine, the system works like this:

[0312] 1. A user (new employee) registers and logs in after completing email authentication.

[0313] 2. The user selects "Machine Operation" in their profile settings and enters their learning goals.

[0314] 3. Based on this information, the server generates a customized machine operation training program and displays it on the terminal.

[0315] 4. When a user enters a question during training, the server uses an AI chatbot to instantly generate an answer and display it on the device.

[0316] 5. The server schedules an online session with an expert, and the user joins the session and asks questions directly.

[0317] 6. Based on the user's progress data, the server generates a progress report and displays it to the user on the terminal.

[0318] 7. User reviews report and plans next learning steps.

[0319] 8. The robot guides the user through the work steps, uses sensors to detect movements and provides appropriate feedback.

[0320] Prompt Sentence Examples

[0321] "Please provide a method for designing an easy-to-use AI interactive robot trainer so that new employees can receive real-time answers to any questions they may have during training on new machine operation."

[0322] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0323] Step 1:

[0324] The user enters their profile information and learning goals, including their name, email address, password, interests, learning goals, etc. The device then sends this information to the server.

[0325] Step 2:

[0326] The server records the information in a user database based on the received user information, generates an email containing an authentication link, and sends it to the user. This allows the server to securely manage the user's profile information and start the authentication process.

[0327] Step 3:

[0328] When the user clicks on the link in the authentication email, the server activates the account, which causes the server to update the user's authentication status and grant access to the learning platform.

[0329] Step 4:

[0330] After logging in, users enter their interests and learning goals on the profile settings page. The device then sends this information back to the server, which then obtains the data needed to generate the most appropriate learning curriculum.

[0331] Step 5:

[0332] Based on the received information, the server uses an AI model to generate an individually customized learning curriculum, which includes learning content that reflects the user's interests and learning goals, and then sends the curriculum to the device and displays it to the user.

[0333] Step 6:

[0334] When a user enters a question or concern that arises during their study into their device, the question is sent to the server, which uses an AI chatbot to instantly generate an answer and send it to the device in real time, allowing users to immediately resolve any doubts they may have while studying.

[0335] Step 7:

[0336] The server periodically receives the user's learning progress data (e.g., completed assignments, test results, and study time). It analyzes the received data and generates a progress report. The generated progress report is sent to the terminal and displayed to the user.

[0337] Step 8:

[0338] The server schedules online sessions with experts or instructors as needed based on the user's learning progress, and the device displays a notification of the online session to the user and provides a session link at the specified time.

[0339] Step 9:

[0340] Once users click on the session link, an online session will begin, allowing for real-time interaction with experts and mentors, allowing users to directly ask questions about specific questions and issues and receive expert answers.

[0341] Step 10:

[0342] The AI-embedded robot guides users through work procedures and uses sensors to detect their movements. When users operate the equipment, the robot provides timely feedback, allowing users to receive effective training in a real-world work environment.

[0343] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0344] This invention relates to an educational platform that utilizes an AI conversational chatbot and emotion recognition engine, and describes how to specifically implement the system to provide a personalized learning experience.

[0345] System configuration

[0346] This system consists of four components: the user, the device, the server, and the emotion engine, which work together to realize education. It also integrates AI chatbots with support from experts and teachers.

[0347] User Registration and Authentication

[0348] 1. A user accesses the educational platform's website or app and enters profile information such as name, email address, and password on the new registration screen.

[0349] 2. The device sends the entered profile information to the server.

[0350] 3. The server stores the user information in a database based on the received profile information.

[0351] 4. The server sends an email containing a verification link to the user's email address.

[0352] 5. The user clicks the link in the verification email to activate their account.

[0353] 6. The server verifies that the user clicked the link and updates the account status to "active."

[0354] Customized educational content

[0355] 1. The user logs in and accesses the profile settings page.

[0356] 2. The user inputs their area of ​​interest or learning goal (e.g., mathematics, high school level, specifically calculus).

[0357] 3. The device sends the user's input information to the server.

[0358] 4. Based on the information received by the server, the AI ​​chatbot algorithm is run to generate a customized learning curriculum.

[0359] 5. The server sends the generated curriculum to the terminal.

[0360] 6. The device displays the curriculum to the user and provides a button to start learning.

[0361] Emotion recognition engine integration

[0362] 1. The emotion engine monitors the user's input, voice, and facial expressions in real time.

[0363] 2. The device sends the user's emotional state data to the emotion engine.

[0364] 3. The emotion engine analyzes the received data and estimates the user's emotional state (e.g., stress, satisfaction, fatigue).

[0365] 4. The server adjusts the learning curriculum and the AI ​​chatbot's responses based on the emotional data obtained from the emotion engine.

[0366] 5. The server optimizes the learning environment and support according to the user's emotional state.

[0367] Interactive learning support

[0368] 1. The user inputs a question or concern that arises during learning (e.g., "Teach me the basics of calculus").

[0369] 2. The device sends the user's question to the server.

[0370] 3. The server analyzes the question received by the AI ​​chatbot and generates an answer.

[0371] 4. The server sends the answer obtained from the AI ​​chatbot to the device.

[0372] 5. The device displays the answers to the user, and also provides a field for entering additional questions if desired.

[0373] Real-time support and feedback

[0374] 1. The server schedules online sessions with experts and teachers (based on the user's learning progress and schedule).

[0375] 2. The server sends a notification to the device containing the session date and time and a link.

[0376] 3. The device displays a notification of the online session to the user.

[0377] 4. The user clicks the session link from the notification at the specified time.

[0378] 5. The server starts the online session and the expert or teacher connects.

[0379] 6. Users can ask questions directly during the session and receive real-time feedback.

[0380] Progress management and evaluation

[0381] 1. The device periodically sends the user's learning progress data (completed assignments, test results, time passage, etc.) to the server.

[0382] 2. The server records the received progress data in a database.

[0383] 3. The server analyzes the progress data and evaluates trends and rate of progress.

[0384] 4. The server generates a progress report based on the user's learning progress.

[0385] 5. The server generates a progress report and sends it to the device.

[0386] 6. The device displays a progress report to the user and suggests next learning steps.

[0387] Specific Examples

[0388] For example, let's say a junior high school student, Mr. A, wants to study mathematics efficiently. In this case, the system works as follows:

[0389] 1. A user (Mr. A) registers and logs in after completing email authentication.

[0390] 2. User (A) selects "High School Mathematics" in the profile settings and enters his / her learning goals.

[0391] 3. The server generates a high school mathematics curriculum based on this information and displays it on the terminal.

[0392] 4. The emotion engine analyzes the user's (person A's) facial expressions and voice to identify their emotional state.

[0393] 5. If the server determines based on emotional data that A is not enjoying the learning experience, it will adjust the curriculum to improve A's interest in learning.

[0394] 6. While studying, a user (Mr. A) types a question: "Please teach me the basics of differential and integral calculus."

[0395] 7. The server uses an AI chatbot to instantly generate a response and display it on the device.

[0396] 8. The server schedules an online session with an expert, and the user (Person A) joins the session and asks questions directly.

[0397] 9. The device sends Mr. A's learning progress data to the server, and the server generates a progress report and sends it to the device.

[0398] 10. User (Person A) reviews the report and plans the next learning steps.

[0399] In this way, the system can provide an individually customized learning experience and realize an advanced educational environment that combines real-time learning support and emotion recognition.

[0400] The processing flow will be explained below.

[0401] Program processing steps

[0402] User Registration and Authentication

[0403] Step 1:

[0404] A user accesses the education platform's website or app and enters profile information such as name, email address, and password on the new registration screen.

[0405] Step 2:

[0406] The device transmits the entered profile information to the server.

[0407] Step 3:

[0408] The server stores user information in a database based on the received profile information.

[0409] Step 4:

[0410] The server sends an email containing a verification link to the user's email address.

[0411] Step 5:

[0412] The user clicks the link in the verification email to activate their account.

[0413] Step 6:

[0414] The server verifies that the user clicked the link and updates the account status to "active."

[0415] Customized educational content

[0416] Step 1:

[0417] User logs in and visits the profile settings page.

[0418] Step 2:

[0419] The user inputs their area of ​​interest or learning goal (e.g., mathematics, high school level, specifically calculus).

[0420] Step 3:

[0421] The terminal transmits the user's input information to the server.

[0422] Step 4:

[0423] Based on the information received by the server, the AI ​​chatbot's algorithm is run to generate a customized learning curriculum.

[0424] Step 5:

[0425] The server transmits the generated curriculum to the terminal.

[0426] Step 6:

[0427] The terminal displays the curriculum to the user and provides a button to start learning.

[0428] Emotion recognition engine integration

[0429] Step 1:

[0430] The emotion engine monitors the user's voice, facial expressions, and input in real time.

[0431] Step 2:

[0432] The terminal transmits the user's emotional state data to the emotion engine.

[0433] Step 3:

[0434] The emotion engine analyzes the received data and estimates the user's emotional state (e.g., stress, satisfaction, fatigue).

[0435] Step 4:

[0436] The server adjusts the learning curriculum and the responses of the AI ​​chatbot based on the emotional data obtained from the emotion engine.

[0437] Step 5:

[0438] The server optimizes the learning environment and support according to the user's emotional state.

[0439] Interactive learning support

[0440] Step 1:

[0441] The user inputs questions or doubts that arise during the study (e.g., "Please teach me the basics of calculus").

[0442] Step 2:

[0443] The terminal sends the user's question to the server.

[0444] Step 3:

[0445] The server analyzes the questions it receives and has the AI ​​chatbot generate answers.

[0446] Step 4:

[0447] The server sends the answer obtained from the AI ​​chatbot to the terminal.

[0448] Step 5:

[0449] The device displays the answers to the user and also provides a field where they can enter additional questions if desired.

[0450] Real-time support and feedback

[0451] Step 1:

[0452] The server schedules online sessions with experts and teachers (based on the user's learning progress and schedule).

[0453] Step 2:

[0454] The server sends a notification to the device containing the session date and time and a link.

[0455] Step 3:

[0456] The terminal displays a notification of the online session to the user.

[0457] Step 4:

[0458] The user clicks the session link from the notification at the specified time.

[0459] Step 5:

[0460] The server initiates the online session, and the expert or teacher connects.

[0461] Step 6:

[0462] Users can ask questions directly during the session and receive real-time feedback.

[0463] Progress management and evaluation

[0464] Step 1:

[0465] The device periodically sends the user's learning progress data (completed assignments, test results, study time) to the server.

[0466] Step 2:

[0467] The server records the received progress data in a database.

[0468] Step 3:

[0469] The server analyzes the progress data and evaluates trends and rate of progress.

[0470] Step 4:

[0471] The server generates a progress report based on the user's learning status.

[0472] Step 5:

[0473] The server generates a progress report and sends it to the device.

[0474] Step 6:

[0475] The device displays progress reports to the user and suggests next learning steps.

[0476] Specific examples

[0477] As a concrete example, let us consider the case where a junior high school student named A wants to study mathematics efficiently.

[0478] User Registration and Authentication

[0479] Step 1:

[0480] A user (Mr. A) registers and enters the necessary information.

[0481] Step 2:

[0482] The terminal sends this information to the server.

[0483] Step 3:

[0484] The server stores the information and sends a verification email.

[0485] Step 4:

[0486] The user (Mr. A) clicks on the link in the verification email to activate the account.

[0487] Customized educational content

[0488] Step 1:

[0489] The user (Mr. A) logs in and sets his / her learning interests and goals.

[0490] Step 2:

[0491] The terminal sends this information to the server.

[0492] Step 3:

[0493] The server generates a high school mathematics curriculum and transmits it to the terminal.

[0494] Step 4:

[0495] The device displays the learning curriculum and Person A begins learning.

[0496] Emotion recognition engine integration

[0497] Step 1:

[0498] The emotion engine analyzes Mr. A's facial expressions and voice to estimate his emotional state.

[0499] Step 2:

[0500] The device sends this data to the emotion engine.

[0501] Step 3:

[0502] The emotion engine sends the analysis results to the server.

[0503] Step 4:

[0504] The server adjusts learning content and feedback based on emotional data.

[0505] Interactive learning support

[0506] Step 1:

[0507] A user (person A) inputs a question such as "Teach me the basics of differential and integral calculus."

[0508] Step 2:

[0509] The terminal sends a question to the server.

[0510] Step 3:

[0511] The server analyzes the question using an AI chatbot and generates an answer.

[0512] Step 4:

[0513] The server sends the answer to the terminal and displays it to Mr. A.

[0514] Real-time support and feedback

[0515] Step 1:

[0516] The server schedules a session between A and the expert and sends a notification.

[0517] Step 2:

[0518] The terminal displays a notification of the session.

[0519] Step 3:

[0520] The user (person A) clicks on the session link and interacts with the expert.

[0521] Progress management and evaluation

[0522] Step 1:

[0523] The device periodically sends Mr. A's progress data to the server.

[0524] Step 2:

[0525] The server analyzes the data and generates a progress report.

[0526] Step 3:

[0527] The server sends the report to the device, and Person A plans his next learning step.

[0528] In this way, a system that integrates an emotion engine provides a personalized learning experience and real-time support.

[0529] Example 2

[0530] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0531] Current learning systems lack the ability to provide personalized learning experiences and real-time support. Furthermore, they often provide a uniform learning curriculum without considering the user's emotional state, which can lead to reduced learning efficiency and a loss of motivation. Furthermore, collaboration with experts and teachers is often not smooth, making it difficult to quickly solve problems. To address these issues, a comprehensive and efficient learning support system is needed.

[0532] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0533] In this invention, the server includes: a means for a user to input individual profile information and learning goals; a means for generating a learning curriculum based on the received user information; a means for transmitting the generated learning curriculum to the user's terminal and displaying it; a means for the user to input questions that arise during learning and for the server to instantly generate answers using AI; a means for the server to schedule online sessions with experts or teachers in real time; a means for transmitting the user's learning progress data from the terminal to the server and for the server to generate a progress report; a means for monitoring the user's facial expressions, input, and voice and analyzing the user's emotional state using an emotion recognition engine; and a means for the server to adjust the learning curriculum and the AI ​​chatbot's answers based on the analyzed emotional state. This makes it possible to provide users with a personalized learning experience and appropriate support, thereby improving learning efficiency.

[0534] "Profile Information" means the personal identification information and information regarding learning goals that a User provides when registering with the System.

[0535] A "learning curriculum" is a personalized learning plan generated by the server based on a user's profile information and learning goals.

[0536] A "terminal" is an electronic device such as a computer, smartphone, or tablet that allows a user to access and operate the system.

[0537] "Server" means a central processing system that receives, stores, and analyzes user profile information, and generates and transmits learning curriculum.

[0538] "AI" is an algorithm that uses artificial intelligence technology to analyze user input data and generate appropriate answers and support.

[0539] An "online session" is a session with video call or chat functionality that allows users to communicate with experts or teachers in real time.

[0540] "Study progress data" is information about a user's learning activities, including completed assignments, test results, study time, and the like.

[0541] An "emotion recognition engine" is software or algorithms that analyze a user's facial expressions, input, and voice to infer their emotional state.

[0542] "Real-time" is a time concept that means immediate or near-immediate data processing and response.

[0543] Hereinafter, embodiments of the present invention will be described in detail.

[0544] User Registration and Authentication

[0545] A user accesses the educational platform's website or app and enters profile information such as name, email address, and password on the new registration screen. The device sends the entered information to the server, which receives it and stores it in a database. After saving, the server sends an email containing a verification link to the user's email address. When the user clicks the verification link, the server updates the account status to "active."

[0546] Customized educational content

[0547] After logging in, the user enters their areas of interest and learning goals. The device sends the input information to the server, which then runs the AI ​​chatbot algorithm based on the received information. This algorithm uses Tensorflow (registered trademark) or PyTorch to generate a customized learning curriculum. The generated curriculum is sent to the device and displayed on the user's screen.

[0548] Emotion recognition engine integration

[0549] The emotion recognition engine monitors the user's input, voice, and facial expressions in real time. Software such as OpenCV and TensorFlow is used to analyze data obtained from the webcam and microphone used by the user during learning. The device sends the acquired emotional data to the emotion recognition engine, which then sends the analyzed data to the server. The server analyzes the emotional data and adjusts the learning curriculum and the responses of the AI ​​chatbot.

[0550] Interactive learning support

[0551] When a user inputs a question that arises during learning, the device sends the question to the server. The server receives the question and uses an AI chatbot to instantly generate an answer. The AI ​​chatbot used uses GPT-3 (registered trademark) or BERT, and the generated answer is sent to the device and displayed to the user. A field is also provided where additional questions can be asked if necessary.

[0552] Real-time support and feedback

[0553] The server schedules online sessions with experts or teachers based on the user's learning progress and schedule. The date, time, and link of the scheduled session are sent to the device, and the user joins the online session via the notification. During the session, the user can ask questions directly and receive real-time feedback from the experts or teachers. Zoom or GOOGLE MEET (registered trademark) are commonly used as video conferencing systems.

[0554] Progress management and evaluation

[0555] The device periodically sends the user's learning progress data to the server. The progress data includes completed assignments, test results, and study time. The server analyzes the received data and uses Python's Pandas and NumPy to evaluate trends and progress speed. After analysis, the server generates a progress report and sends it to the device. The device displays the progress report to the user and suggests the next learning step.

[0556] Specific examples

[0557] For example, if a junior high school student named A wants to efficiently improve their math studies, the system operates as follows: The user (A) registers and logs in after verifying their email address. They select "High School Mathematics" in their profile settings and enter their learning goals. The server generates a curriculum based on this information and displays it on their device. The emotion recognition engine analyzes A's facial expressions and voice to identify their emotional state. The server adjusts the curriculum based on the emotional data to increase their interest in learning. If the user types a question such as "Teach me the basics of calculus," the server uses an AI chatbot to generate an answer and displays it on their device. The server also schedules an online session with an expert, allowing the user to participate and ask questions directly. The device sends learning progress data to the server, which then generates a progress report and sends it to the device. The user reviews the report and plans their next learning steps. In this way, it is possible to provide individually customized learning experiences and real-time support.

[0558] Prompt Sentence Examples

[0559] "Generate a customized learning curriculum for high school mathematics calculus."

[0560] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0561] Step 1:

[0562] The user accesses the educational platform and enters their profile information (name, email address, password) on the new registration screen.

[0563] Input: Name, email address, and password provided by the user.

[0564] Output: New registration request.

[0565] Step 2:

[0566] The device transmits the entered profile information to the server.

[0567] Input: Profile information entered by the user.

[0568] Output: New registration request received on the server side.

[0569] Step 3:

[0570] The server stores the received profile information in a database and sends an email containing a verification link to the user's email address.

[0571] Input: Received profile information.

[0572] Data manipulation: Create a new user record in the database.

[0573] Output: Sending verification email.

[0574] Step 4:

[0575] The user clicks the link in the verification email to activate their account.

[0576] Input: Verification email.

[0577] Output: Authentication page accessed.

[0578] Step 5:

[0579] The server verifies that the user clicked the link and updates the account status to "active."

[0580] Input: Authentication link click information.

[0581] Data manipulation: Update the user status in the database.

[0582] Output: Account enabled.

[0583] Step 6:

[0584] Users log in and enter their interests and learning goals.

[0585] Input: User login information and learning goal (e.g., mathematics, high school level, specifically calculus).

[0586] Output: Learning goal setting request.

[0587] Step 7:

[0588] The terminal transmits the user's input information to the server.

[0589] Input: Learning objectives set by the user.

[0590] Output: Sends a learning goal setting request to the server.

[0591] Step 8:

[0592] Based on the information received by the server, the AI ​​chatbot's algorithm is run to generate a customized learning curriculum.

[0593] Input: User learning goals and AI algorithms (using TensorFlow or PyTorch).

[0594] Data Computing: Using generative AI models to build personalized learning curricula.

[0595] Output: A customized learning curriculum.

[0596] Step 9:

[0597] The server transmits the generated learning curriculum to the terminal.

[0598] Input: The generated learning curriculum.

[0599] Output: Send curriculum to device.

[0600] Step 10:

[0601] The terminal displays the learning curriculum to the user and provides a button to start learning.

[0602] Input: Learning curriculum received from the server.

[0603] Output: Display the curriculum on the learning screen and provide a button to start learning.

[0604] Step 11:

[0605] The emotion engine monitors the user's input, voice, and facial expressions in real time, and the device transmits that data.

[0606] Input: User facial expression, input, and voice data.

[0607] Data processing: Data extraction for sentiment analysis.

[0608] Output: Emotion data sent to the server.

[0609] Step 12:

[0610] The server analyzes the data obtained from the emotion engine and adjusts the learning curriculum and the responses of the AI ​​chatbot based on the user's emotional state.

[0611] Input: Parsed emotion data.

[0612] Data Computing: Aligning learning curriculum and AI chatbots.

[0613] Output: Generation of tailored curriculum and response content.

[0614] Step 13:

[0615] When a user inputs a question that arises during learning, the terminal sends the question to the server.

[0616] Input: A question from the user.

[0617] Output: Sends a query to the server.

[0618] Step 14:

[0619] The server analyzes the questions it receives and has the AI ​​chatbot generate answers.

[0620] Input: The question received.

[0621] Data Computation: Generate answers using generative AI models (such as GPT-3 or BERT).

[0622] Output: The generated answer.

[0623] Step 15:

[0624] The server sends the generated answer to the terminal, which displays it to the user.

[0625] Input: The generated answer.

[0626] Output: Send and display the answer to the terminal.

[0627] Step 16:

[0628] The server schedules online sessions with experts and teachers and sends the session date, time and link to the device.

[0629] Input: User's learning progress data.

[0630] Data calculation: Session scheduling at the right time.

[0631] Output: Sending session notifications.

[0632] Step 17:

[0633] The terminal displays a notification of the online session to the user, and the user clicks on the session link from the notification at the specified time.

[0634] Input: The session notification received from the server.

[0635] Output: Display a notification and provide a link.

[0636] Step 18:

[0637] The server initiates the online session, allowing users to ask questions to the teacher and receive real-time feedback.

[0638] Input: User questions and teacher feedback.

[0639] Output: Real-time Q&A.

[0640] Step 19:

[0641] The terminal transmits the user's learning progress data to the server, which generates a progress report.

[0642] Input: Learning progress data.

[0643] Data Calculation: Analyze progress data using Python's Pandas and NumPy.

[0644] Output: Generates a progress report.

[0645] Step 20:

[0646] The server generates a progress report and sends it to the terminal, which displays it to the user and suggests the next learning step.

[0647] Input: The generated progress report.

[0648] Output: Report sent to terminal and displayed, suggesting next steps.

[0649] (Application example 2)

[0650] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0651] Conventional educational platforms and training systems struggle to provide individually customized learning experiences, particularly in providing appropriate learning support in real time based on the learner's emotional state. They also lack the ability to instantly connect with experts and educators, and require flexible responses based on the learner's progress. This can lead to learners being unable to progress efficiently, resulting in a decline in the quality of their learning.

[0652] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for a user to input individual profile information and learning goals; means for generating a learning curriculum based on the user information received by the server; means for transmitting the generated learning curriculum to the user's terminal and displaying it; means for the user to input questions that arise during learning and for the server to instantly generate answers using AI; means for the server to schedule online sessions with experts and educators in real time; means for transmitting the user's learning progress data from the terminal to the server and for the server to generate a progress report; means for the server to analyze the user's emotional state and adjust the learning curriculum based on the emotional data; means for estimating the user's emotions using an emotion recognition engine; and means for the AI ​​chatbot to adjust the dialogue according to the user's emotional state. This provides an individually customized learning experience that takes the user's emotional state into consideration, enabling real-time support and appropriate adjustment of the learning curriculum.

[0653] 1. "User" means an individual or organization that uses the educational platform to carry out learning activities.

[0654] 2. "Profile Information" refers to individual information entered by a user, such as name, email address, and learning goals.

[0655] 3. A "learning curriculum" is a set of learning plans and content generated based on a user's learning goals.

[0656] 4. "Server" is a computer system that processes requests from users, generates learning curricula, and manages progress data.

[0657] 5. "Terminal" means a device through which a User accesses the educational platform and uses the learning curriculum.

[0658] 6. An "AI chatbot" is a program that uses artificial intelligence to generate instant answers to user questions.

[0659] 7. An "emotion recognition engine" is a technology that analyzes a user's facial expressions and voice data to estimate their emotional state.

[0660] 8. "Emotions" refers to the user's psychological state during learning, such as stress, satisfaction, fatigue, etc.

[0661] 9. An "expert" is a person with advanced knowledge and experience in a particular field who provides guidance and support to users.

[0662] 10. "Online Session" means a form of support provided via video call or chat in real time with an expert or educator via a server.

[0663] 11. "Progress Data" means data that indicates a User's learning progress, including completed assignments and test results.

[0664] 12. "Progress Report" means a report of a User's learning status generated based on the Progress Data.

[0665] System configuration

[0666] This embodiment of the system consists of a user, a terminal, a server, and an emotion recognition engine. The server performs the main processing and interacts with the user through the terminal. The server provides an educational platform, generating individualized programs, managing study goals, answering questions, and providing emotion-based support.

[0667] User Registration and Authentication

[0668] 1. A user accesses the educational platform and enters profile information such as name, email address, and password.

[0669] 2. The device sends this profile information to the server, which stores it in a database and sends a verification email to the user's email address. The user clicks on the link in the email to activate their account.

[0670] Customized educational content

[0671] 1. After logging in, the user enters their areas of interest and learning goals.

[0672] 2. The device sends the user's input information to the server, which then uses the AI ​​chatbot's algorithm to generate a customized learning curriculum, which is then sent to the device and displayed to the user.

[0673] Emotion recognition engine integration

[0674] 1. The emotion recognition engine monitors the user's facial expressions and voice data in real time.

[0675] 2. The device sends the user's emotional data to the emotion recognition engine, which then provides the analysis results to the server.

[0676] 3. The server adjusts the learning curriculum and the AI ​​chatbot's responses based on the emotional data.

[0677] Interactive learning support

[0678] 1. The user types in a question while studying.

[0679] 2. The device sends the question to the server, where the AI ​​chatbot analyzes it and generates an answer, which is then sent to the device and displayed to the user.

[0680] Real-time support and feedback

[0681] 1. The server schedules an online session with an expert or educator. A notification of the session is sent to the user's device and displayed. The online session starts at the specified time, allowing the user to receive real-time support.

[0682] Progress management and evaluation

[0683] 1. The device periodically sends the user's learning progress data to the server. The server analyzes the received data and generates a progress report. The report is then sent to the device and displayed to the user.

[0684] Specific examples

[0685] For example, consider a new employee undergoing work training in a factory. Using this system, the new employee inputs the necessary information and is provided with a curriculum that includes the proper work procedures. Employee emotions are also monitored, and if stress or confusion is detected, an AI chatbot will provide appropriate support.

[0686] Example prompt sentence:

[0687] "Are you ready to take the next step? Answer 'yes' or 'no'."

[0688] Step 1: Gather your tools

[0689] "AI Chatbot: My emotional state is stressed. How can I help?"

[0690] The system combines an individually tailored learning experience with real-time support, enabling learners to learn efficiently and effectively.

[0691] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0692] Step 1:

[0693] A user accesses the educational platform and enters their individual profile information (such as name, email address, and password). This information is sent to the server via their device. The server receives the information, stores it in a database, and sends the user an email containing an authentication link.

[0694] Input: Profile information entered by the user

[0695] Output: Send authentication email, save user information to database

[0696] Operation: The server performs the function of generating and sending an authentication email.

[0697] Step 2:

[0698] The user clicks on the link in the verification email they received to activate their account. The server confirms this action and updates the account status to "Active."

[0699] Input: User clicks authentication link

[0700] Output: Account status update

[0701] Behavior: The server updates the account status when the user clicks the authentication link.

[0702] Step 3:

[0703] The user logs in and enters their areas of interest and learning goals. The device sends this information to the server, which then uses the AI ​​chatbot's algorithm to generate a personalized curriculum. The generated curriculum is then sent to the device and displayed to the user.

[0704] Input: User interests and learning goals

[0705] Output: Display of generated learning curriculum

[0706] How it works: The server uses an AI chatbot to generate a learning curriculum and send it to the device.

[0707] Step 4:

[0708] The emotion recognition engine monitors the user's facial expressions and voice in real time, and the emotion data is sent from the device to the server, which then analyzes the data to identify the user's emotional state.

[0709] Input: User's facial expressions and voice data

[0710] Output: Identification of emotional state (e.g., stress, satisfaction, fatigue)

[0711] How it works: The emotion recognition engine analyzes the data and infers the emotional state.

[0712] Step 5:

[0713] The server adjusts the learning curriculum and the AI ​​chatbot's responses based on the emotional data, optimizing the curriculum to make learning more enjoyable for users depending on their emotional state.

[0714] Input: Parsed emotion data

[0715] Output: Tailored learning curriculum and AI chatbot answers

[0716] How it works: The server uses generative AI models to tailor content and dialogue based on emotion data.

[0717] Step 6:

[0718] The user enters a question that arises during the learning process, and the device sends the question to the server, which uses an AI chatbot to instantly generate an answer, which is then sent to the device and displayed to the user.

[0719] Input: User question

[0720] Output: Answer by AI chatbot

[0721] How it works: The server analyzes the question, generates an appropriate answer, and sends it to the device.

[0722] Step 7:

[0723] The server schedules online sessions with experts and educators. Session notifications are sent to the device and displayed to the user. The user joins the session at the designated time and receives real-time feedback.

[0724] Input: User's learning progress and schedule

[0725] Output: Online session schedule and notifications

[0726] How it works: The server manages the schedule and sends notifications.

[0727] Step 8:

[0728] The device periodically sends the user's learning progress data to the server, which analyzes the progress data and generates a progress report, which is sent to the device and displayed to the user.

[0729] Input: Learning progress data

[0730] Output: Progress report

[0731] How it works: The server analyzes the progress data and generates a report.

[0732] This allows users to receive a personalized learning experience, with real-time support and an optimized curriculum.

[0733] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0734] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0735] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0736] [Second embodiment]

[0737] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0738] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0739] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0740] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0741] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0742] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0743] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0744] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0745] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0746] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0747] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0748] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0749] This invention relates to an educational platform that utilizes AI interactive chatbots, and describes specific implementation methods for the system to provide individually customized learning experiences.

[0750] System configuration

[0751] This system consists of three components: the user, the device, and the server, and these components work together to realize education. It also integrates AI chatbots with support from experts and teachers.

[0752] User Registration and Authentication

[0753] 1. The user accesses the educational platform's website or app and enters profile information such as name, email address, and password on the new registration screen.

[0754] 2. The terminal sends the entered information to the server.

[0755] 3. The server uses this information to record the user information in its database and sends the user an email containing an authentication link.

[0756] 4. When the user clicks on the link in the verification email, the account is activated on the server side.

[0757] Customized educational content

[0758] 1. After logging in, users enter their interests and learning goals into the profile settings page.

[0759] 2. The terminal sends this input information to the server.

[0760] 3. Based on the received information, the server uses an AI chatbot to generate an individually customized learning curriculum.

[0761] 4. The server sends the generated curriculum to the terminal, where it is displayed to the user.

[0762] Interactive learning support

[0763] 1. When a user has a question or concern that arises during their study, they send the question to the server via their terminal.

[0764] 2. The server analyzes the received question using an AI chatbot and instantly generates an answer.

[0765] 3. The server sends the generated answer to the device, providing the user with a real-time answer, and may redirect the question to an expert if necessary.

[0766] Real-time support and feedback

[0767] 1. The server schedules online sessions with experts and teachers based on the user's learning progress, etc.

[0768] 2. The device displays a notification of the online session to the user and provides the session link at the specified time.

[0769] 3. When the designated session time arrives, the user clicks on the notification link to begin a real-time conversation with the expert or teacher.

[0770] Progress management and evaluation

[0771] 1. The device periodically sends the user's learning progress data (e.g., completed assignments, test results, study time) to the server.

[0772] 2. The server records the received progress data in a database and analyzes it.

[0773] 3. The server generates a progress report based on the analysis results and sends it to the device.

[0774] 4. The device displays a progress report to the user, who can use the report to plan their next learning steps.

[0775] Specific Examples

[0776] For example, let's say a junior high school student, Mr. A, wants to study mathematics efficiently. In this case, the system works as follows:

[0777] 1. A user (Mr. A) registers and logs in after completing email authentication.

[0778] 2. User (A) selects "High School Mathematics" in the profile settings and enters his / her learning goals.

[0779] 3. The server generates a high school mathematics curriculum based on this information and displays it on the terminal.

[0780] 4. While studying, a user (Mr. A) types a question: "Please teach me the basics of differential and integral calculus."

[0781] 5. The server uses an AI chatbot to instantly generate a response and display it on the device.

[0782] 6. The server schedules an online session with an expert, and the user (Person A) joins the session and asks questions directly.

[0783] 7. The device sends Mr. A's learning progress data to the server, and the server generates a progress report and sends it to the device.

[0784] 8. User (A) reviews the report and plans the next learning steps.

[0785] In this way, the system provides an individually customized learning experience, enabling efficient and effective learning with the support of experts.

[0786] The processing flow will be explained below.

[0787] Program processing steps

[0788] User Registration and Authentication

[0789] Step 1:

[0790] A user accesses the education platform's website or app and enters profile information such as name, email address, and password on the new registration screen.

[0791] Step 2:

[0792] The device transmits the entered profile information to the server.

[0793] Step 3:

[0794] The server stores user information in a database based on the received profile information.

[0795] Step 4:

[0796] The server sends an email containing a verification link to the user's email address.

[0797] Step 5:

[0798] The user clicks the link in the verification email to activate their account.

[0799] Step 6:

[0800] The server verifies that the user clicked the link and updates the account status to "active."

[0801] Customized educational content

[0802] Step 1:

[0803] User logs in and visits the profile settings page.

[0804] Step 2:

[0805] The user inputs their area of ​​interest or learning goal (e.g., mathematics, high school level, specifically calculus).

[0806] Step 3:

[0807] The terminal transmits the user's input information to the server.

[0808] Step 4:

[0809] Based on the information received by the server, the AI ​​chatbot's algorithm is run to generate a customized learning curriculum.

[0810] Step 5:

[0811] The server transmits the generated curriculum to the terminal.

[0812] Step 6:

[0813] The terminal displays the curriculum to the user and provides a button to start learning.

[0814] Interactive learning support

[0815] Step 1:

[0816] The user inputs questions or doubts that arise during the study (e.g., "Please teach me the basics of calculus").

[0817] Step 2:

[0818] The terminal sends the user's question to the server.

[0819] Step 3:

[0820] The server analyzes the questions it receives and has the AI ​​chatbot generate answers.

[0821] Step 4:

[0822] The server sends the answer obtained from the AI ​​chatbot to the terminal.

[0823] Step 5:

[0824] The device displays the answers to the user and also provides a field where they can enter additional questions if desired.

[0825] Real-time support and feedback

[0826] Step 1:

[0827] The server schedules online sessions with experts and teachers (based on the user's learning progress and schedule).

[0828] Step 2:

[0829] The server sends a notification to the device containing the session date and time and a link.

[0830] Step 3:

[0831] The terminal displays a notification of the online session to the user.

[0832] Step 4:

[0833] The user clicks the session link from the notification at the specified time.

[0834] Step 5:

[0835] The server initiates the online session, and the expert or teacher connects.

[0836] Step 6:

[0837] Users can ask questions directly during the session and receive real-time feedback.

[0838] Progress management and evaluation

[0839] Step 1:

[0840] The device periodically sends the user's learning progress data (completed assignments, test results, time elapsed, etc.) to the server.

[0841] Step 2:

[0842] The server records the received progress data in a database.

[0843] Step 3:

[0844] The server analyzes the progress data and evaluates trends and rate of progress.

[0845] Step 4:

[0846] The server generates a progress report based on the user's learning status.

[0847] Step 5:

[0848] The server generates a progress report and sends it to the device.

[0849] Step 6:

[0850] The device displays progress reports to the user and suggests next learning steps.

[0851] Example 1

[0852] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0853] Traditional educational platforms lack the ability to customize content to meet individual learning needs and goals, making it difficult for users to learn efficiently and effectively. Furthermore, the mechanisms for providing real-time support from experts and teachers are incomplete, limiting the means by which users can get immediate answers to questions that arise during their studies. Progress management and assessment must also be done manually, placing a burden on users.

[0854] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0855] In this invention, the server includes: means for a user to input individual profile information and learning goals; means for the terminal to encrypt the input information and transmit it to the server; means for generating an individually customized learning curriculum based on the user information received by the server; means for transmitting the generated learning curriculum to the user's terminal and displaying it; means for the user to input questions that arise during learning and for the terminal to transmit the questions to the server; means for the server to instantly generate answers to the questions received by the server using an AI model; means for the server to schedule online sessions with experts or teachers in real time; means for the terminal to display notifications of the online sessions to the user; means for the terminal to transmit the user's learning progress data to the server; means for the server to analyze the received learning progress data and generate a progress report; and means for the terminal to transmit the generated progress report to the terminal and display it to the user. This provides a customized learning experience that meets the user's individual learning needs, enables real-time question resolution and direct communication with experts, and automates progress management and evaluation, thereby enabling efficient and effective learning for the user.

[0856] "User" refers to an individual who uses the educational platform and who enters individual profile information and learning goals.

[0857] "Terminal" refers to a device such as a PC or smartphone, which is a means for sending information from the user to the server and receiving and displaying information from the server.

[0858] The "server" is a computer system that controls the entire system, including generating a learning curriculum based on received user information, answering user questions, and analyzing progress data.

[0859] "Profile Information" means personal identification information such as name, email address, and password that a User enters when registering on the Education Platform.

[0860] "Learning goals" refer to the specific learning outcomes or objectives that a user wishes to achieve, and serve as the basis for the system to generate a customized learning curriculum.

[0861] "Learning curriculum" refers to an individual learning schedule and learning content generated based on a user's profile information and learning goals.

[0862] A "question" is something that a user inputs when they are unsure about something they are unsure about while studying, and is something that requires an answer.

[0863] An "AI model" refers to an algorithm or system that uses artificial intelligence technology to analyze data and generate answers to user questions.

[0864] An "expert" refers to an individual or occupation that has advanced knowledge and experience in a specific field of study and provides expert answers to users' questions and inquiries.

[0865] "Online Session" refers to an opportunity for interaction and instruction with an expert or teacher conducted in real time via the Internet.

[0866] "Notifications" means information sent by the System to Users, including schedules for online sessions and important updates.

[0867] "Study progress data" is data that indicates how far a user has progressed in their studies, and includes information such as completed assignments, test results, and study time.

[0868] A "progress report" is a report summarizing the results of an analysis of a user's learning progress data, and serves as reference material when the user makes future learning plans.

[0869] This invention relates to an educational platform that utilizes AI interactive chatbots, and describes specific implementation methods for the system to provide individually customized learning experiences.

[0870] System configuration

[0871] This system consists of three entities: the user, the terminal, and the server. The specific roles and operations of each entity are explained below.

[0872] User Registration and Authentication

[0873] A user accesses the educational platform's website or app and enters profile information such as name, email address, and password on the new registration screen. The device encrypts the entered information and sends it to the server via HTTPS. The server decrypts the received user information and stores it in a back-end SQL database (e.g., MySQL or PostgreSQL). The server then sends an email containing an authentication link to the user's email address. This authentication is performed using an email sending system such as SendGrid or Amazon SES. When the user clicks the link in the authentication email, the server verifies the token in the authentication link and updates the database to activate the account.

[0874] Customized educational content

[0875] After logging in, users enter their interests and learning goals on the profile settings page. The device encrypts this information and sends it to the server. The server then sends the received user information to an AI model (e.g., OpenAI's GPT-4) to generate an individually customized learning curriculum. This curriculum is sent to the device in JSON format, and the device displays it to the user.

[0876] Interactive learning support

[0877] When a user inputs a question or concern that arises during learning, the device sends the question to the server. The server sends the question to the AI ​​chatbot (generative AI model), which analyzes it in real time and generates an answer. The server then sends the generated answer to the device, which displays it to the user.

[0878] Example prompt sentence:

[0879] User: Teach me the basics of calculus.

[0880] AI Chatbot: Calculus is an important subject in high school mathematics. First of all, differentiation is the operation of finding the rate of change of a function. For example, the derivative of y = x^2 is dy / dx = 2x. On the other hand, integration is the operation of finding the cumulative amount of a function, and the integral of y = x^2 is ∫x^2 dx = (1 / 3)x^3 + C. Please let me know if there are any specific topics or problems you would like to know about.

[0881] Real-time support and feedback

[0882] The server schedules online sessions with experts or teachers based on the user's learning progress. The device displays a notification of the online session to the user and presents a session link at the specified time. The user clicks the link at the specified session time to interact with the expert or teacher in real time.

[0883] Progress management and evaluation

[0884] The device periodically sends the user's learning progress data (e.g., completed assignments, test results, and study time) to the server. The server records the received progress data in a database and performs data analysis. This analysis can be performed using Python tools such as Pandas or NumPy. The server generates a progress report based on the analysis results and sends it to the device. The device displays the progress report to the user, who can use it to plan their next learning steps.

[0885] Specific examples

[0886] For example, consider the case where a junior high school student, Person A, is working on a new mathematics topic, "Calculus." The user (Person A) registers and logs in after email authentication. Person A enters that he or she is interested in "Calculus" in his or her profile settings, and the server uses this information to generate an individually customized curriculum, which is sent to the device and displayed. If Person A enters a question while studying, such as "Teach me the basics of calculus," the server uses an AI model to instantly generate an answer and displays it on the device. The server also schedules an online session with an expert, with Person A interacting in real time at the specified time. The device sends Person A's learning progress data to the server, which generates a progress report and sends it to the device, where Person A can review the report and plan his or her next learning steps.

[0887] In this way, this system allows users to customize their learning experience and receive real-time expert support, making learning efficient and effective.

[0888] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0889] Step 1:

[0890] Users access the educational platform's website or app and enter profile information such as their name, email address, and password on the new registration screen.

[0891] Input: User profile information such as name, email address, and password.

[0892] Output: Encrypted user information.

[0893] What happens: A user fills out a form using a browser or app and clicks the "Register" button.

[0894] Step 2:

[0895] The terminal encrypts the entered information and sends it to the server via the HTTPS protocol.

[0896] Input: Profile information entered by the user.

[0897] Output: Encrypted user information sent to the server.

[0898] Specific operation: The terminal encrypts input data using SSL / TLS and sends an HTTPS request to the server.

[0899] Step 3:

[0900] The server decrypts the received user information and stores it in a back-end SQL database (e.g. MySQL or PostgreSQL).

[0901] Input: Encrypted user information.

[0902] Output: User information stored in the database.

[0903] Specific operation: The server decrypts the received data using SSL / TLS and inserts the user information into the database using an SQL query.

[0904] Step 4:

[0905] The server sends an email containing an authentication link to the user's email address. For example, SendGrid or Amazon SES is used as the email sending system.

[0906] Input: The user's email address.

[0907] Output: The authentication email sent to the user.

[0908] Specific operation: The server uses the email API to generate email content and send an authentication link to the specified email address.

[0909] Step 5:

[0910] The user checks their mailbox and clicks on the link in the verification email.

[0911] Input: The link in the verification email.

[0912] Output: The authentication request sent to the server.

[0913] What happens: The user opens the email and clicks on a link, causing the browser to send a request to the server.

[0914] Step 6:

[0915] The server validates the token in the authentication link and updates its database to validate the user account.

[0916] Input: Token for authentication link.

[0917] Output: Activated user account information.

[0918] What happens: The server validates the link's token and updates the user record in the database using an SQL query.

[0919] Step 7:

[0920] After logging in, users enter their interests and learning goals on the profile settings page.

[0921] Input: Information such as interests and learning goals.

[0922] Output: Encrypted learning objective information.

[0923] Specific behavior: A user logs in, enters information on a settings page, and clicks the save button.

[0924] Step 8:

[0925] The terminal encrypts this input information and sends it to the server.

[0926] Input: User-entered interest and learning goal information.

[0927] Output: Encrypted learning objective information sent to the server.

[0928] Specific operation: The terminal encrypts input data using SSL / TLS and sends an HTTPS request to the server.

[0929] Step 9:

[0930] The server sends the received user information to an AI model (e.g., OpenAI's GPT-4) to generate an individually customized learning curriculum.

[0931] Input: User's learning goals, profile information.

[0932] Output: The generated learning curriculum.

[0933] Specific operation: The server sends user information to the AI ​​model and generates a curriculum from the model's response.

[0934] Step 10:

[0935] The server sends the generated curriculum in JSON format to the terminal, which displays it to the user.

[0936] Input: The generated learning curriculum.

[0937] Output: The curriculum that is displayed to the user.

[0938] Specific operation: The server sends curriculum data in JSON format to the terminal, which parses it and displays it on the user interface.

[0939] Step 11:

[0940] When the user inputs any doubts or questions that arise during the study, the terminal sends this question to the server.

[0941] Input: User's doubt or question.

[0942] Output: The query data sent to the server.

[0943] Specific operation: The user enters a question and clicks the send button, causing the device to send the data to the server.

[0944] Step 12:

[0945] The server sends the question to the AI ​​model, which analyzes it and generates an answer in real time.

[0946] Input: The user's question.

[0947] Output: The generated answer.

[0948] How it works: The server passes a question to the AI ​​model and receives the answer generated by the model.

[0949] Step 13:

[0950] The server generates a response and sends it to the terminal, which displays it to the user.

[0951] Input: The generated answer.

[0952] Output: The answer that is displayed to the user.

[0953] Specific operation: The server sends the response data to the terminal, which parses it and displays it on the user interface.

[0954] Step 14:

[0955] The server schedules online sessions with experts and teachers based on the user's learning progress.

[0956] Input: User's learning progress data.

[0957] Output: Online session schedule.

[0958] Specific behavior: The server analyzes the progress data and reserves an online session at the appropriate time.

[0959] Step 15:

[0960] The terminal displays a notification of the online session to the user and presents the session link at the specified time.

[0961] Enter: Schedule an online session.

[0962] Output: The notification and session link that is displayed to the user.

[0963] Specific operation: The terminal receives the session schedule and displays a notification and link on the user interface.

[0964] Step 16:

[0965] Users click on the link at the designated session time to interact with the expert or teacher in real time.

[0966] Input: Online session link.

[0967] Output: Communication with experts and teachers.

[0968] What happens: The user clicks on a link and connects with an expert or teacher via a video conferencing platform or similar.

[0969] Step 17:

[0970] The terminal periodically transmits the user's learning progress data to the server.

[0971] Input: Learning progress data (e.g. completed assignments, test results, study time).

[0972] Output: Progress data sent to the server.

[0973] Specific operation: The device collects progress data at regular intervals, encrypts it, and sends it to the server.

[0974] Step 18:

[0975] The server records the received progress data in a database and performs data analysis.

[0976] Input: Progress data.

[0977] Output: Parsed data.

[0978] Specific operation: The server stores progress data in an SQL database and analyzes it using data analysis tools (e.g., Python's Pandas or NumPy).

[0979] Step 19:

[0980] The server generates a progress report based on the analysis results and sends it to the terminal.

[0981] Input: Analysis results.

[0982] Output: The generated progress report.

[0983] Specific operation: The server aggregates the analysis results, generates a progress report including text and graphs, and sends it to the device in JSON format.

[0984] Step 20:

[0985] The device displays a progress report to the user, who can use it to plan their next learning steps.

[0986] Input: Progress report.

[0987] Output: The report that is displayed to the user.

[0988] Specific operation: The device parses the received report data and displays it visually in the user interface. The user can then check the content and set their next learning goal or plan.

[0989] (Application example 1)

[0990] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0991] Traditional education platforms lack the flexibility to accommodate individual learning requirements. Furthermore, in-factory training lacks a way to accept questions in real time and provide immediate answers. Furthermore, the lack of an environment for direct interaction with experts and instructors during training often results in insufficient learning outcomes. This makes it particularly difficult to provide efficient training in a real-world work environment for new and existing employees.

[0992] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0993] In this invention, the server includes: means for a user to input individual profile information and learning goals; means for generating a learning curriculum based on the user information received by the server; means for transmitting the generated learning curriculum to the user's terminal and displaying it; means for the user to input questions that arise during learning and for the server to instantly generate answers using AI; means for the server to schedule online sessions with experts or instructors in real time; means for transmitting the user's learning progress data from the terminal to the server and for the server to generate progress reports; means for a robot incorporating AI functions to support the user's training and provide on-site work procedures; means for inputting training status and questions to the robot in real time using the terminal and for the robot to instantly respond; and means including a sensor for detecting the user's actions when operating equipment and providing feedback at appropriate times. This allows users to receive individually customized learning experiences, enabling efficient and effective learning through real-time question and answer sessions and dialogue with experts.

[0994] "User" refers to the entity that uses the educational platform, who sets individual learning goals and manages their learning progress.

[0995] "Profile information" refers collectively to personal identification information and study-related information entered by a user.

[0996] "Learning goal" refers to the learning objective or goal that a user wants to achieve.

[0997] "Device" refers to the device (e.g., smartphone, tablet, or computer) used by a User to access the Education Platform.

[0998] "Server" refers to the central processing unit that receives, processes and manages information from users.

[0999] "Learning Curriculum" refers to a set of learning content and plans generated based on a user's profile information and learning goals.

[1000] "AI" refers to artificial intelligence technology, which has the ability to analyze and generate information interactively.

[1001] "Real-time" refers to instantaneous processing and response.

[1002] An "expert" is an individual who has advanced knowledge or skills in a particular field.

[1003] "Instructor" refers to an individual whose role is to provide education and training to users.

[1004] "Online Session" means an interactive educational or training session conducted via the Internet.

[1005] "Progress Data" refers to data and information that indicates a user's learning or training progress.

[1006] "Progress Report" refers to a report summarizing and analyzing a user's learning progress.

[1007] A "robot" is an automated mechanical device that incorporates AI to support user training and learning.

[1008] A "work procedure" refers to a series of steps or methods for accomplishing a particular task.

[1009] A "sensor" refers to a device that detects physical variables (e.g., movement or position) and acquires them as data.

[1010] This invention is an educational platform system using robots with built-in AI functions, which provides individually customized learning experiences and streamlines training within factories. The system mainly consists of a server, terminals, and users. The details are explained below.

[1011] User Registration and Authentication

[1012] A user accesses the educational platform's website or app and enters profile information such as name, email address, and password on the new registration screen. The device sends the entered information to the server, which records it in a database. An email containing a verification link is sent to the user, and when the user clicks the link in the verification email, the account is activated.

[1013] Customized educational content

[1014] After logging in, users enter their interests and learning goals on a profile setting page. The device sends this information to the server, which then uses an AI model to generate an individually customized learning curriculum based on the received information. The generated curriculum is then sent to the device and displayed to the user.

[1015] Interactive learning support

[1016] When a user inputs a question or concern that arises during learning, the question is sent to the server via the device. The server uses an AI chatbot to instantly generate an answer and provides it to the user via the device in real time. If necessary, the question may be redirected to an expert.

[1017] Real-time support and feedback

[1018] The server schedules online sessions with experts or instructors based on the user's learning progress, etc. The device displays a notification of the online session to the user and presents a session link at the specified time. When the specified session time arrives, the user clicks the notification link to begin a real-time dialogue with the expert or instructor.

[1019] Progress management and evaluation

[1020] The device periodically sends the user's learning progress data (e.g., completed assignments, test results, study time) to the server. The server records the received progress data in a database and analyzes it. The server generates a progress report based on the analysis results and sends it to the device to display to the user. The user can use the report to plan their next learning steps.

[1021] Robotic training support

[1022] The robot, which incorporates AI functions, supports user training and provides guidance on on-site work procedures. Training status and questions are input to the robot in real time using a terminal, and the robot responds immediately. In addition, when the user operates equipment, the robot detects the user's movements using built-in sensors and provides feedback at the appropriate time.

[1023] Specific examples

[1024] For example, if a new employee needs to learn how to operate a new machine, the system works like this:

[1025] 1. A user (new employee) registers and logs in after completing email authentication.

[1026] 2. The user selects "Machine Operation" in their profile settings and enters their learning goals.

[1027] 3. Based on this information, the server generates a customized machine operation training program and displays it on the terminal.

[1028] 4. When a user enters a question during training, the server uses an AI chatbot to instantly generate an answer and display it on the device.

[1029] 5. The server schedules an online session with an expert, and the user joins the session and asks questions directly.

[1030] 6. Based on the user's progress data, the server generates a progress report and displays it to the user on the terminal.

[1031] 7. User reviews report and plans next learning steps.

[1032] 8. The robot guides the user through the work steps, uses sensors to detect movements and provides appropriate feedback.

[1033] Prompt Sentence Examples

[1034] "Please provide a method for designing an easy-to-use AI interactive robot trainer so that new employees can receive real-time answers to any questions they may have during training on new machine operation."

[1035] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1036] Step 1:

[1037] The user enters their profile information and learning goals, including their name, email address, password, interests, learning goals, etc. The device then sends this information to the server.

[1038] Step 2:

[1039] The server records the information in a user database based on the received user information, generates an email containing an authentication link, and sends it to the user. This allows the server to securely manage the user's profile information and start the authentication process.

[1040] Step 3:

[1041] When the user clicks on the link in the authentication email, the server activates the account, which causes the server to update the user's authentication status and grant access to the learning platform.

[1042] Step 4:

[1043] After logging in, users enter their interests and learning goals on the profile settings page. The device then sends this information back to the server, which then obtains the data needed to generate the most appropriate learning curriculum.

[1044] Step 5:

[1045] Based on the received information, the server uses an AI model to generate an individually customized learning curriculum, which includes learning content that reflects the user's interests and learning goals, and then sends the curriculum to the device and displays it to the user.

[1046] Step 6:

[1047] When a user enters a question or concern that arises during their study into their device, the question is sent to the server, which uses an AI chatbot to instantly generate an answer and send it to the device in real time, allowing users to immediately resolve any doubts they may have while studying.

[1048] Step 7:

[1049] The server periodically receives the user's learning progress data (e.g., completed assignments, test results, and study time). It analyzes the received data and generates a progress report. The generated progress report is sent to the terminal and displayed to the user.

[1050] Step 8:

[1051] The server schedules online sessions with experts or instructors as needed based on the user's learning progress, and the device displays a notification of the online session to the user and provides a session link at the specified time.

[1052] Step 9:

[1053] Once users click on the session link, an online session will begin, allowing for real-time interaction with experts and mentors, allowing users to directly ask questions about specific questions and issues and receive expert answers.

[1054] Step 10:

[1055] The AI-embedded robot guides users through work procedures and uses sensors to detect their movements. When users operate the equipment, the robot provides timely feedback, allowing users to receive effective training in a real-world work environment.

[1056] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1057] This invention relates to an educational platform that utilizes an AI conversational chatbot and emotion recognition engine, and describes how to specifically implement the system to provide a personalized learning experience.

[1058] System configuration

[1059] This system consists of four components: the user, the device, the server, and the emotion engine, which work together to realize education. It also integrates AI chatbots with support from experts and teachers.

[1060] User Registration and Authentication

[1061] 1. A user accesses the educational platform's website or app and enters profile information such as name, email address, and password on the new registration screen.

[1062] 2. The device sends the entered profile information to the server.

[1063] 3. The server stores the user information in a database based on the received profile information.

[1064] 4. The server sends an email containing a verification link to the user's email address.

[1065] 5. The user clicks the link in the verification email to activate their account.

[1066] 6. The server verifies that the user clicked the link and updates the account status to "active."

[1067] Customized educational content

[1068] 1. The user logs in and accesses the profile settings page.

[1069] 2. The user inputs their area of ​​interest or learning goal (e.g., mathematics, high school level, specifically calculus).

[1070] 3. The device sends the user's input information to the server.

[1071] 4. Based on the information received by the server, the AI ​​chatbot algorithm is run to generate a customized learning curriculum.

[1072] 5. The server sends the generated curriculum to the terminal.

[1073] 6. The device displays the curriculum to the user and provides a button to start learning.

[1074] Emotion recognition engine integration

[1075] 1. The emotion engine monitors the user's input, voice, and facial expressions in real time.

[1076] 2. The device sends the user's emotional state data to the emotion engine.

[1077] 3. The emotion engine analyzes the received data and estimates the user's emotional state (e.g., stress, satisfaction, fatigue).

[1078] 4. The server adjusts the learning curriculum and the AI ​​chatbot's responses based on the emotional data obtained from the emotion engine.

[1079] 5. The server optimizes the learning environment and support according to the user's emotional state.

[1080] Interactive learning support

[1081] 1. The user inputs a question or concern that arises during learning (e.g., "Teach me the basics of calculus").

[1082] 2. The device sends the user's question to the server.

[1083] 3. The server analyzes the question received by the AI ​​chatbot and generates an answer.

[1084] 4. The server sends the answer obtained from the AI ​​chatbot to the device.

[1085] 5. The device displays the answers to the user, and also provides a field for entering additional questions if desired.

[1086] Real-time support and feedback

[1087] 1. The server schedules online sessions with experts and teachers (based on the user's learning progress and schedule).

[1088] 2. The server sends a notification to the device containing the session date and time and a link.

[1089] 3. The device displays a notification of the online session to the user.

[1090] 4. The user clicks the session link from the notification at the specified time.

[1091] 5. The server starts the online session and the expert or teacher connects.

[1092] 6. Users can ask questions directly during the session and receive real-time feedback.

[1093] Progress management and evaluation

[1094] 1. The device periodically sends the user's learning progress data (completed assignments, test results, time passage, etc.) to the server.

[1095] 2. The server records the received progress data in a database.

[1096] 3. The server analyzes the progress data and evaluates trends and rate of progress.

[1097] 4. The server generates a progress report based on the user's learning progress.

[1098] 5. The server generates a progress report and sends it to the device.

[1099] 6. The device displays a progress report to the user and suggests next learning steps.

[1100] Specific Examples

[1101] For example, let's say a junior high school student, Mr. A, wants to study mathematics efficiently. In this case, the system works as follows:

[1102] 1. A user (Mr. A) registers and logs in after completing email authentication.

[1103] 2. User (A) selects "High School Mathematics" in the profile settings and enters his / her learning goals.

[1104] 3. The server generates a high school mathematics curriculum based on this information and displays it on the terminal.

[1105] 4. The emotion engine analyzes the user's (person A's) facial expressions and voice to identify their emotional state.

[1106] 5. If the server determines based on emotional data that A is not enjoying the learning experience, it will adjust the curriculum to improve A's interest in learning.

[1107] 6. While studying, a user (Mr. A) types a question: "Please teach me the basics of differential and integral calculus."

[1108] 7. The server uses an AI chatbot to instantly generate a response and display it on the device.

[1109] 8. The server schedules an online session with an expert, and the user (Person A) joins the session and asks questions directly.

[1110] 9. The device sends Mr. A's learning progress data to the server, and the server generates a progress report and sends it to the device.

[1111] 10. User (Person A) reviews the report and plans the next learning steps.

[1112] In this way, the system can provide an individually customized learning experience and realize an advanced educational environment that combines real-time learning support and emotion recognition.

[1113] The processing flow will be explained below.

[1114] Program processing steps

[1115] User Registration and Authentication

[1116] Step 1:

[1117] A user accesses the education platform's website or app and enters profile information such as name, email address, and password on the new registration screen.

[1118] Step 2:

[1119] The device transmits the entered profile information to the server.

[1120] Step 3:

[1121] The server stores user information in a database based on the received profile information.

[1122] Step 4:

[1123] The server sends an email containing a verification link to the user's email address.

[1124] Step 5:

[1125] The user clicks the link in the verification email to activate their account.

[1126] Step 6:

[1127] The server verifies that the user clicked the link and updates the account status to "active."

[1128] Customized educational content

[1129] Step 1:

[1130] User logs in and visits the profile settings page.

[1131] Step 2:

[1132] The user inputs their area of ​​interest or learning goal (e.g., mathematics, high school level, specifically calculus).

[1133] Step 3:

[1134] The terminal transmits the user's input information to the server.

[1135] Step 4:

[1136] Based on the information received by the server, the AI ​​chatbot's algorithm is run to generate a customized learning curriculum.

[1137] Step 5:

[1138] The server transmits the generated curriculum to the terminal.

[1139] Step 6:

[1140] The terminal displays the curriculum to the user and provides a button to start learning.

[1141] Emotion recognition engine integration

[1142] Step 1:

[1143] The emotion engine monitors the user's voice, facial expressions, and input in real time.

[1144] Step 2:

[1145] The terminal transmits the user's emotional state data to the emotion engine.

[1146] Step 3:

[1147] The emotion engine analyzes the received data and estimates the user's emotional state (e.g., stress, satisfaction, fatigue).

[1148] Step 4:

[1149] The server adjusts the learning curriculum and the responses of the AI ​​chatbot based on the emotional data obtained from the emotion engine.

[1150] Step 5:

[1151] The server optimizes the learning environment and support according to the user's emotional state.

[1152] Interactive learning support

[1153] Step 1:

[1154] The user inputs questions or doubts that arise during the study (e.g., "Please teach me the basics of calculus").

[1155] Step 2:

[1156] The terminal sends the user's question to the server.

[1157] Step 3:

[1158] The server analyzes the questions it receives and has the AI ​​chatbot generate answers.

[1159] Step 4:

[1160] The server sends the answer obtained from the AI ​​chatbot to the terminal.

[1161] Step 5:

[1162] The device displays the answers to the user and also provides a field where they can enter additional questions if desired.

[1163] Real-time support and feedback

[1164] Step 1:

[1165] The server schedules online sessions with experts and teachers (based on the user's learning progress and schedule).

[1166] Step 2:

[1167] The server sends a notification to the device containing the session date and time and a link.

[1168] Step 3:

[1169] The terminal displays a notification of the online session to the user.

[1170] Step 4:

[1171] The user clicks the session link from the notification at the specified time.

[1172] Step 5:

[1173] The server initiates the online session, and the expert or teacher connects.

[1174] Step 6:

[1175] Users can ask questions directly during the session and receive real-time feedback.

[1176] Progress management and evaluation

[1177] Step 1:

[1178] The device periodically sends the user's learning progress data (completed assignments, test results, study time) to the server.

[1179] Step 2:

[1180] The server records the received progress data in a database.

[1181] Step 3:

[1182] The server analyzes the progress data and evaluates trends and rate of progress.

[1183] Step 4:

[1184] The server generates a progress report based on the user's learning status.

[1185] Step 5:

[1186] The server generates a progress report and sends it to the device.

[1187] Step 6:

[1188] The device displays progress reports to the user and suggests next learning steps.

[1189] Specific examples

[1190] As a concrete example, let us consider the case where a junior high school student named A wants to study mathematics efficiently.

[1191] User Registration and Authentication

[1192] Step 1:

[1193] A user (Mr. A) registers and enters the necessary information.

[1194] Step 2:

[1195] The terminal sends this information to the server.

[1196] Step 3:

[1197] The server stores the information and sends a verification email.

[1198] Step 4:

[1199] The user (Mr. A) clicks on the link in the verification email to activate the account.

[1200] Customized educational content

[1201] Step 1:

[1202] The user (Mr. A) logs in and sets his / her learning interests and goals.

[1203] Step 2:

[1204] The terminal sends this information to the server.

[1205] Step 3:

[1206] The server generates a high school mathematics curriculum and transmits it to the terminal.

[1207] Step 4:

[1208] The device displays the learning curriculum and Person A begins learning.

[1209] Emotion recognition engine integration

[1210] Step 1:

[1211] The emotion engine analyzes Mr. A's facial expressions and voice to estimate his emotional state.

[1212] Step 2:

[1213] The device sends this data to the emotion engine.

[1214] Step 3:

[1215] The emotion engine sends the analysis results to the server.

[1216] Step 4:

[1217] The server adjusts learning content and feedback based on emotional data.

[1218] Interactive learning support

[1219] Step 1:

[1220] A user (person A) inputs a question such as "Teach me the basics of differential and integral calculus."

[1221] Step 2:

[1222] The terminal sends a question to the server.

[1223] Step 3:

[1224] The server analyzes the question using an AI chatbot and generates an answer.

[1225] Step 4:

[1226] The server sends the answer to the terminal and displays it to Mr. A.

[1227] Real-time support and feedback

[1228] Step 1:

[1229] The server schedules a session between A and the expert and sends a notification.

[1230] Step 2:

[1231] The terminal displays a notification of the session.

[1232] Step 3:

[1233] The user (person A) clicks on the session link and interacts with the expert.

[1234] Progress management and evaluation

[1235] Step 1:

[1236] The device periodically sends Mr. A's progress data to the server.

[1237] Step 2:

[1238] The server analyzes the data and generates a progress report.

[1239] Step 3:

[1240] The server sends the report to the device, and Person A plans his next learning step.

[1241] In this way, a system that integrates an emotion engine provides a personalized learning experience and real-time support.

[1242] Example 2

[1243] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1244] Current learning systems lack the ability to provide personalized learning experiences and real-time support. Furthermore, they often provide a uniform learning curriculum without considering the user's emotional state, which can lead to reduced learning efficiency and a loss of motivation. Furthermore, collaboration with experts and teachers is often not smooth, making it difficult to quickly solve problems. To address these issues, a comprehensive and efficient learning support system is needed.

[1245] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1246] In this invention, the server includes: a means for a user to input individual profile information and learning goals; a means for generating a learning curriculum based on the received user information; a means for transmitting the generated learning curriculum to the user's terminal and displaying it; a means for the user to input questions that arise during learning and for the server to instantly generate answers using AI; a means for the server to schedule online sessions with experts or teachers in real time; a means for transmitting the user's learning progress data from the terminal to the server and for the server to generate a progress report; a means for monitoring the user's facial expressions, input, and voice and analyzing the user's emotional state using an emotion recognition engine; and a means for the server to adjust the learning curriculum and the AI ​​chatbot's answers based on the analyzed emotional state. This makes it possible to provide users with a personalized learning experience and appropriate support, thereby improving learning efficiency.

[1247] "Profile Information" means the personal identification information and information regarding learning goals that a User provides when registering with the System.

[1248] A "learning curriculum" is a personalized learning plan generated by the server based on a user's profile information and learning goals.

[1249] A "terminal" is an electronic device such as a computer, smartphone, or tablet that allows a user to access and operate the system.

[1250] "Server" means a central processing system that receives, stores, and analyzes user profile information, and generates and transmits learning curriculum.

[1251] "AI" is an algorithm that uses artificial intelligence technology to analyze user input data and generate appropriate answers and support.

[1252] An "online session" is a session with video call or chat functionality that allows users to communicate with experts or teachers in real time.

[1253] "Study progress data" is information about a user's learning activities, including completed assignments, test results, study time, and the like.

[1254] An "emotion recognition engine" is software or algorithms that analyze a user's facial expressions, input, and voice to infer their emotional state.

[1255] "Real-time" is a time concept that means immediate or near-immediate data processing and response.

[1256] Hereinafter, embodiments of the present invention will be described in detail.

[1257] User Registration and Authentication

[1258] A user accesses the educational platform's website or app and enters profile information such as name, email address, and password on the new registration screen. The device sends the entered information to the server, which receives it and stores it in a database. After saving, the server sends an email containing a verification link to the user's email address. When the user clicks the verification link, the server updates the account status to "active."

[1259] Customized educational content

[1260] After logging in, the user enters their areas of interest and learning goals. The device sends the input information to the server, which then runs the AI ​​chatbot algorithm based on the received information. This algorithm uses TensorFlow or PyTorch to generate a customized learning curriculum. The generated curriculum is sent to the device and displayed on the user's screen.

[1261] Emotion recognition engine integration

[1262] The emotion recognition engine monitors the user's input, voice, and facial expressions in real time. Software such as OpenCV and TensorFlow is used to analyze data obtained from the webcam and microphone used by the user during learning. The device sends the acquired emotional data to the emotion recognition engine, which then sends the analyzed data to the server. The server analyzes the emotional data and adjusts the learning curriculum and the responses of the AI ​​chatbot.

[1263] Interactive learning support

[1264] When a user enters a question that arises during learning, the device sends the question to the server. The server receives the question and uses an AI chatbot to instantly generate an answer. The AI ​​chatbot used uses GPT-3 or BERT, and the generated answer is sent to the device and displayed to the user. A field is also provided where additional questions can be asked if necessary.

[1265] Real-time support and feedback

[1266] The server schedules online sessions with experts or teachers based on the user's learning progress and schedule. The date, time, and link of the scheduled session are sent to the device, and the user joins the online session via the notification. During the session, the user can ask questions directly and receive real-time feedback from the experts or teachers. Zoom or Google (registered trademark) is commonly used as the video conferencing system.

[1267] Progress management and evaluation

[1268] The device periodically sends the user's learning progress data to the server. The progress data includes completed assignments, test results, and study time. The server analyzes the received data and uses Python's Pandas and NumPy to evaluate trends and progress speed. After analysis, the server generates a progress report and sends it to the device. The device displays the progress report to the user and suggests the next learning step.

[1269] Specific examples

[1270] For example, if a junior high school student named A wants to efficiently improve their math studies, the system operates as follows: The user (A) registers and logs in after verifying their email address. They select "High School Mathematics" in their profile settings and enter their learning goals. The server generates a curriculum based on this information and displays it on their device. The emotion recognition engine analyzes A's facial expressions and voice to identify their emotional state. The server adjusts the curriculum based on the emotional data to increase their interest in learning. If the user types a question such as "Teach me the basics of calculus," the server uses an AI chatbot to generate an answer and displays it on their device. The server also schedules an online session with an expert, allowing the user to participate and ask questions directly. The device sends learning progress data to the server, which then generates a progress report and sends it to the device. The user reviews the report and plans their next learning steps. In this way, it is possible to provide individually customized learning experiences and real-time support.

[1271] Prompt Sentence Examples

[1272] "Generate a customized learning curriculum for high school mathematics calculus."

[1273] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1274] Step 1:

[1275] The user accesses the educational platform and enters their profile information (name, email address, password) on the new registration screen.

[1276] Input: Name, email address, and password provided by the user.

[1277] Output: New registration request.

[1278] Step 2:

[1279] The device transmits the entered profile information to the server.

[1280] Input: Profile information entered by the user.

[1281] Output: New registration request received on the server side.

[1282] Step 3:

[1283] The server stores the received profile information in a database and sends an email containing a verification link to the user's email address.

[1284] Input: Received profile information.

[1285] Data manipulation: Create a new user record in the database.

[1286] Output: Sending verification email.

[1287] Step 4:

[1288] The user clicks the link in the verification email to activate their account.

[1289] Input: Verification email.

[1290] Output: Authentication page accessed.

[1291] Step 5:

[1292] The server verifies that the user clicked the link and updates the account status to "active."

[1293] Input: Authentication link click information.

[1294] Data manipulation: Update the user status in the database.

[1295] Output: Account enabled.

[1296] Step 6:

[1297] Users log in and enter their interests and learning goals.

[1298] Input: User login information and learning goal (e.g., mathematics, high school level, specifically calculus).

[1299] Output: Learning goal setting request.

[1300] Step 7:

[1301] The terminal transmits the user's input information to the server.

[1302] Input: Learning objectives set by the user.

[1303] Output: Sends a learning goal setting request to the server.

[1304] Step 8:

[1305] Based on the information received by the server, the AI ​​chatbot's algorithm is run to generate a customized learning curriculum.

[1306] Input: User learning goals and AI algorithms (using TensorFlow or PyTorch).

[1307] Data Computing: Using generative AI models to build personalized learning curricula.

[1308] Output: A customized learning curriculum.

[1309] Step 9:

[1310] The server transmits the generated learning curriculum to the terminal.

[1311] Input: The generated learning curriculum.

[1312] Output: Send curriculum to device.

[1313] Step 10:

[1314] The terminal displays the learning curriculum to the user and provides a button to start learning.

[1315] Input: Learning curriculum received from the server.

[1316] Output: Display the curriculum on the learning screen and provide a button to start learning.

[1317] Step 11:

[1318] The emotion engine monitors the user's input, voice, and facial expressions in real time, and the device transmits that data.

[1319] Input: User facial expression, input, and voice data.

[1320] Data processing: Data extraction for sentiment analysis.

[1321] Output: Emotion data sent to the server.

[1322] Step 12:

[1323] The server analyzes the data obtained from the emotion engine and adjusts the learning curriculum and the responses of the AI ​​chatbot based on the user's emotional state.

[1324] Input: Parsed emotion data.

[1325] Data Computing: Aligning learning curriculum and AI chatbots.

[1326] Output: Generation of tailored curriculum and response content.

[1327] Step 13:

[1328] When a user inputs a question that arises during learning, the terminal sends the question to the server.

[1329] Input: A question from the user.

[1330] Output: Sends a query to the server.

[1331] Step 14:

[1332] The server analyzes the questions it receives and has the AI ​​chatbot generate answers.

[1333] Input: The question received.

[1334] Data Computation: Generate answers using generative AI models (such as GPT-3 or BERT).

[1335] Output: The generated answer.

[1336] Step 15:

[1337] The server sends the generated answer to the terminal, which displays it to the user.

[1338] Input: The generated answer.

[1339] Output: Send and display the answer to the terminal.

[1340] Step 16:

[1341] The server schedules online sessions with experts and teachers and sends the session date, time and link to the device.

[1342] Input: User's learning progress data.

[1343] Data calculation: Session scheduling at the right time.

[1344] Output: Sending session notifications.

[1345] Step 17:

[1346] The terminal displays a notification of the online session to the user, and the user clicks on the session link from the notification at the specified time.

[1347] Input: The session notification received from the server.

[1348] Output: Display a notification and provide a link.

[1349] Step 18:

[1350] The server initiates the online session, allowing users to ask questions to the teacher and receive real-time feedback.

[1351] Input: User questions and teacher feedback.

[1352] Output: Real-time Q&A.

[1353] Step 19:

[1354] The terminal transmits the user's learning progress data to the server, which generates a progress report.

[1355] Input: Learning progress data.

[1356] Data Calculation: Analyze progress data using Python's Pandas and NumPy.

[1357] Output: Generates a progress report.

[1358] Step 20:

[1359] The server generates a progress report and sends it to the terminal, which displays it to the user and suggests the next learning step.

[1360] Input: The generated progress report.

[1361] Output: Report sent to terminal and displayed, suggesting next steps.

[1362] (Application example 2)

[1363] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1364] Conventional educational platforms and training systems struggle to provide individually customized learning experiences, particularly in providing appropriate learning support in real time based on the learner's emotional state. They also lack the ability to instantly connect with experts and educators, and require flexible responses based on the learner's progress. This can lead to learners being unable to progress efficiently, resulting in a decline in the quality of their learning.

[1365] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for a user to input individual profile information and learning goals; means for generating a learning curriculum based on the user information received by the server; means for transmitting the generated learning curriculum to the user's terminal and displaying it; means for the user to input questions that arise during learning and for the server to instantly generate answers using AI; means for the server to schedule online sessions with experts and educators in real time; means for transmitting the user's learning progress data from the terminal to the server and for the server to generate a progress report; means for the server to analyze the user's emotional state and adjust the learning curriculum based on the emotional data; means for estimating the user's emotions using an emotion recognition engine; and means for the AI ​​chatbot to adjust the dialogue according to the user's emotional state. This provides an individually customized learning experience that takes the user's emotional state into consideration, enabling real-time support and appropriate adjustment of the learning curriculum.

[1366] 1. "User" means an individual or organization that uses the educational platform to carry out learning activities.

[1367] 2. "Profile Information" refers to individual information entered by a user, such as name, email address, and learning goals.

[1368] 3. A "learning curriculum" is a set of learning plans and content generated based on a user's learning goals.

[1369] 4. "Server" is a computer system that processes requests from users, generates learning curricula, and manages progress data.

[1370] 5. "Terminal" means a device through which a User accesses the educational platform and uses the learning curriculum.

[1371] 6. An "AI chatbot" is a program that uses artificial intelligence to generate instant answers to user questions.

[1372] 7. An "emotion recognition engine" is a technology that analyzes a user's facial expressions and voice data to estimate their emotional state.

[1373] 8. "Emotions" refers to the user's psychological state during learning, such as stress, satisfaction, fatigue, etc.

[1374] 9. An "expert" is a person with advanced knowledge and experience in a particular field who provides guidance and support to users.

[1375] 10. "Online Session" means a form of support provided via video call or chat in real time with an expert or educator via a server.

[1376] 11. "Progress Data" means data that indicates a User's learning progress, including completed assignments and test results.

[1377] 12. "Progress Report" means a report of a User's learning status generated based on the Progress Data.

[1378] System configuration

[1379] This embodiment of the system consists of a user, a terminal, a server, and an emotion recognition engine. The server performs the main processing and interacts with the user through the terminal. The server provides an educational platform, generating individualized programs, managing study goals, answering questions, and providing emotion-based support.

[1380] User Registration and Authentication

[1381] 1. A user accesses the educational platform and enters profile information such as name, email address, and password.

[1382] 2. The device sends this profile information to the server, which stores it in a database and sends a verification email to the user's email address. The user clicks on the link in the email to activate their account.

[1383] Customized educational content

[1384] 1. After logging in, the user enters their areas of interest and learning goals.

[1385] 2. The device sends the user's input information to the server, which then uses the AI ​​chatbot's algorithm to generate a customized learning curriculum, which is then sent to the device and displayed to the user.

[1386] Emotion recognition engine integration

[1387] 1. The emotion recognition engine monitors the user's facial expressions and voice data in real time.

[1388] 2. The device sends the user's emotional data to the emotion recognition engine, which then provides the analysis results to the server.

[1389] 3. The server adjusts the learning curriculum and the AI ​​chatbot's responses based on the emotional data.

[1390] Interactive learning support

[1391] 1. The user types in a question while studying.

[1392] 2. The device sends the question to the server, where the AI ​​chatbot analyzes it and generates an answer, which is then sent to the device and displayed to the user.

[1393] Real-time support and feedback

[1394] 1. The server schedules an online session with an expert or educator. A notification of the session is sent to the user's device and displayed. The online session starts at the specified time, allowing the user to receive real-time support.

[1395] Progress management and evaluation

[1396] 1. The device periodically sends the user's learning progress data to the server. The server analyzes the received data and generates a progress report. The report is then sent to the device and displayed to the user.

[1397] Specific examples

[1398] For example, consider a new employee undergoing work training in a factory. Using this system, the new employee inputs the necessary information and is provided with a curriculum that includes the proper work procedures. Employee emotions are also monitored, and if stress or confusion is detected, an AI chatbot will provide appropriate support.

[1399] Example prompt sentence:

[1400] "Are you ready to take the next step? Answer 'yes' or 'no'."

[1401] Step 1: Gather your tools

[1402] "AI Chatbot: My emotional state is stressed. How can I help?"

[1403] The system combines an individually tailored learning experience with real-time support, enabling learners to learn efficiently and effectively.

[1404] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1405] Step 1:

[1406] A user accesses the educational platform and enters their individual profile information (such as name, email address, and password). This information is sent to the server via their device. The server receives the information, stores it in a database, and sends the user an email containing an authentication link.

[1407] Input: Profile information entered by the user

[1408] Output: Send authentication email, save user information to database

[1409] Operation: The server performs the function of generating and sending an authentication email.

[1410] Step 2:

[1411] The user clicks on the link in the verification email they received to activate their account. The server confirms this action and updates the account status to "Active."

[1412] Input: User clicks authentication link

[1413] Output: Account status update

[1414] Behavior: The server updates the account status when the user clicks the authentication link.

[1415] Step 3:

[1416] The user logs in and enters their areas of interest and learning goals. The device sends this information to the server, which then uses the AI ​​chatbot's algorithm to generate a personalized curriculum. The generated curriculum is then sent to the device and displayed to the user.

[1417] Input: User interests and learning goals

[1418] Output: Display of generated learning curriculum

[1419] How it works: The server uses an AI chatbot to generate a learning curriculum and send it to the device.

[1420] Step 4:

[1421] The emotion recognition engine monitors the user's facial expressions and voice in real time, and the emotion data is sent from the device to the server, which then analyzes the data to identify the user's emotional state.

[1422] Input: User's facial expressions and voice data

[1423] Output: Identification of emotional state (e.g., stress, satisfaction, fatigue)

[1424] How it works: The emotion recognition engine analyzes the data and infers the emotional state.

[1425] Step 5:

[1426] The server adjusts the learning curriculum and the AI ​​chatbot's responses based on the emotional data, optimizing the curriculum to make learning more enjoyable for users depending on their emotional state.

[1427] Input: Parsed emotion data

[1428] Output: Tailored learning curriculum and AI chatbot answers

[1429] How it works: The server uses generative AI models to tailor content and dialogue based on emotion data.

[1430] Step 6:

[1431] The user enters a question that arises during the learning process, and the device sends the question to the server, which uses an AI chatbot to instantly generate an answer, which is then sent to the device and displayed to the user.

[1432] Input: User question

[1433] Output: Answer by AI chatbot

[1434] How it works: The server analyzes the question, generates an appropriate answer, and sends it to the device.

[1435] Step 7:

[1436] The server schedules online sessions with experts and educators. Session notifications are sent to the device and displayed to the user. The user joins the session at the designated time and receives real-time feedback.

[1437] Input: User's learning progress and schedule

[1438] Output: Online session schedule and notifications

[1439] How it works: The server manages the schedule and sends notifications.

[1440] Step 8:

[1441] The device periodically sends the user's learning progress data to the server, which analyzes the progress data and generates a progress report, which is sent to the device and displayed to the user.

[1442] Input: Learning progress data

[1443] Output: Progress report

[1444] How it works: The server analyzes the progress data and generates a report.

[1445] This allows users to receive a personalized learning experience, with real-time support and an optimized curriculum.

[1446] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1447] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1448] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1449] [Third embodiment]

[1450] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1451] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1452] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1453] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1454] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1455] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1456] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1457] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1458] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1459] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1460] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1461] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1462] This invention relates to an educational platform that utilizes AI interactive chatbots, and describes specific implementation methods for the system to provide individually customized learning experiences.

[1463] System configuration

[1464] This system consists of three components: the user, the device, and the server, and these components work together to realize education. It also integrates AI chatbots with support from experts and teachers.

[1465] User Registration and Authentication

[1466] 1. The user accesses the educational platform's website or app and enters profile information such as name, email address, and password on the new registration screen.

[1467] 2. The terminal sends the entered information to the server.

[1468] 3. The server uses this information to record the user information in its database and sends the user an email containing an authentication link.

[1469] 4. When the user clicks on the link in the verification email, the account is activated on the server side.

[1470] Customized educational content

[1471] 1. After logging in, users enter their interests and learning goals into the profile settings page.

[1472] 2. The terminal sends this input information to the server.

[1473] 3. Based on the received information, the server uses an AI chatbot to generate an individually customized learning curriculum.

[1474] 4. The server sends the generated curriculum to the terminal, where it is displayed to the user.

[1475] Interactive learning support

[1476] 1. When a user has a question or concern that arises during their study, they send the question to the server via their terminal.

[1477] 2. The server analyzes the received question using an AI chatbot and instantly generates an answer.

[1478] 3. The server sends the generated answer to the device, providing the user with a real-time answer, and may redirect the question to an expert if necessary.

[1479] Real-time support and feedback

[1480] 1. The server schedules online sessions with experts and teachers based on the user's learning progress, etc.

[1481] 2. The device displays a notification of the online session to the user and provides the session link at the specified time.

[1482] 3. When the designated session time arrives, the user clicks on the notification link to begin a real-time conversation with the expert or teacher.

[1483] Progress management and evaluation

[1484] 1. The device periodically sends the user's learning progress data (e.g., completed assignments, test results, study time) to the server.

[1485] 2. The server records the received progress data in a database and analyzes it.

[1486] 3. The server generates a progress report based on the analysis results and sends it to the device.

[1487] 4. The device displays a progress report to the user, who can use the report to plan their next learning steps.

[1488] Specific Examples

[1489] For example, let's say a junior high school student, Mr. A, wants to study mathematics efficiently. In this case, the system works as follows:

[1490] 1. A user (Mr. A) registers and logs in after completing email authentication.

[1491] 2. User (A) selects "High School Mathematics" in the profile settings and enters his / her learning goals.

[1492] 3. The server generates a high school mathematics curriculum based on this information and displays it on the terminal.

[1493] 4. While studying, a user (Mr. A) types a question: "Please teach me the basics of differential and integral calculus."

[1494] 5. The server uses an AI chatbot to instantly generate a response and display it on the device.

[1495] 6. The server schedules an online session with an expert, and the user (Person A) joins the session and asks questions directly.

[1496] 7. The device sends Mr. A's learning progress data to the server, and the server generates a progress report and sends it to the device.

[1497] 8. User (A) reviews the report and plans the next learning steps.

[1498] In this way, the system provides an individually customized learning experience, enabling efficient and effective learning with the support of experts.

[1499] The processing flow will be explained below.

[1500] Program processing steps

[1501] User Registration and Authentication

[1502] Step 1:

[1503] A user accesses the education platform's website or app and enters profile information such as name, email address, and password on the new registration screen.

[1504] Step 2:

[1505] The device transmits the entered profile information to the server.

[1506] Step 3:

[1507] The server stores user information in a database based on the received profile information.

[1508] Step 4:

[1509] The server sends an email containing a verification link to the user's email address.

[1510] Step 5:

[1511] The user clicks the link in the verification email to activate their account.

[1512] Step 6:

[1513] The server verifies that the user clicked the link and updates the account status to "active."

[1514] Customized educational content

[1515] Step 1:

[1516] User logs in and visits the profile settings page.

[1517] Step 2:

[1518] The user inputs their area of ​​interest or learning goal (e.g., mathematics, high school level, specifically calculus).

[1519] Step 3:

[1520] The terminal transmits the user's input information to the server.

[1521] Step 4:

[1522] Based on the information received by the server, the AI ​​chatbot's algorithm is run to generate a customized learning curriculum.

[1523] Step 5:

[1524] The server transmits the generated curriculum to the terminal.

[1525] Step 6:

[1526] The terminal displays the curriculum to the user and provides a button to start learning.

[1527] Interactive learning support

[1528] Step 1:

[1529] The user inputs questions or doubts that arise during the study (e.g., "Please teach me the basics of calculus").

[1530] Step 2:

[1531] The terminal sends the user's question to the server.

[1532] Step 3:

[1533] The server analyzes the questions it receives and has the AI ​​chatbot generate answers.

[1534] Step 4:

[1535] The server sends the answer obtained from the AI ​​chatbot to the terminal.

[1536] Step 5:

[1537] The device displays the answers to the user and also provides a field where they can enter additional questions if desired.

[1538] Real-time support and feedback

[1539] Step 1:

[1540] The server schedules online sessions with experts and teachers (based on the user's learning progress and schedule).

[1541] Step 2:

[1542] The server sends a notification to the device containing the session date and time and a link.

[1543] Step 3:

[1544] The terminal displays a notification of the online session to the user.

[1545] Step 4:

[1546] The user clicks the session link from the notification at the specified time.

[1547] Step 5:

[1548] The server initiates the online session, and the expert or teacher connects.

[1549] Step 6:

[1550] Users can ask questions directly during the session and receive real-time feedback.

[1551] Progress management and evaluation

[1552] Step 1:

[1553] The device periodically sends the user's learning progress data (completed assignments, test results, time elapsed, etc.) to the server.

[1554] Step 2:

[1555] The server records the received progress data in a database.

[1556] Step 3:

[1557] The server analyzes the progress data and evaluates trends and rate of progress.

[1558] Step 4:

[1559] The server generates a progress report based on the user's learning status.

[1560] Step 5:

[1561] The server generates a progress report and sends it to the device.

[1562] Step 6:

[1563] The device displays progress reports to the user and suggests next learning steps.

[1564] Example 1

[1565] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1566] Traditional educational platforms lack the ability to customize content to meet individual learning needs and goals, making it difficult for users to learn efficiently and effectively. Furthermore, the mechanisms for providing real-time support from experts and teachers are incomplete, limiting the means by which users can get immediate answers to questions that arise during their studies. Progress management and assessment must also be done manually, placing a burden on users.

[1567] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1568] In this invention, the server includes: means for a user to input individual profile information and learning goals; means for the terminal to encrypt the input information and transmit it to the server; means for generating an individually customized learning curriculum based on the user information received by the server; means for transmitting the generated learning curriculum to the user's terminal and displaying it; means for the user to input questions that arise during learning and for the terminal to transmit the questions to the server; means for the server to instantly generate answers to the questions received by the server using an AI model; means for the server to schedule online sessions with experts or teachers in real time; means for the terminal to display notifications of the online sessions to the user; means for the terminal to transmit the user's learning progress data to the server; means for the server to analyze the received learning progress data and generate a progress report; and means for the terminal to transmit the generated progress report to the terminal and display it to the user. This provides a customized learning experience that meets the user's individual learning needs, enables real-time question resolution and direct communication with experts, and automates progress management and evaluation, thereby enabling efficient and effective learning for the user.

[1569] "User" refers to an individual who uses the educational platform and who enters individual profile information and learning goals.

[1570] "Terminal" refers to a device such as a PC or smartphone, which is a means for sending information from the user to the server and receiving and displaying information from the server.

[1571] The "server" is a computer system that controls the entire system, including generating a learning curriculum based on received user information, answering user questions, and analyzing progress data.

[1572] "Profile Information" means personal identification information such as name, email address, and password that a User enters when registering on the Education Platform.

[1573] "Learning goals" refer to the specific learning outcomes or objectives that a user wishes to achieve, and serve as the basis for the system to generate a customized learning curriculum.

[1574] "Learning curriculum" refers to an individual learning schedule and learning content generated based on a user's profile information and learning goals.

[1575] A "question" is something that a user inputs when they are unsure about something they are unsure about while studying, and is something that requires an answer.

[1576] An "AI model" refers to an algorithm or system that uses artificial intelligence technology to analyze data and generate answers to user questions.

[1577] An "expert" refers to an individual or occupation that has advanced knowledge and experience in a specific field of study and provides expert answers to users' questions and inquiries.

[1578] "Online Session" refers to an opportunity for interaction and instruction with an expert or teacher conducted in real time via the Internet.

[1579] "Notifications" means information sent by the System to Users, including schedules for online sessions and important updates.

[1580] "Study progress data" is data that indicates how far a user has progressed in their studies, and includes information such as completed assignments, test results, and study time.

[1581] A "progress report" is a report summarizing the results of an analysis of a user's learning progress data, and serves as reference material when the user makes future learning plans.

[1582] This invention relates to an educational platform that utilizes AI interactive chatbots, and describes specific implementation methods for the system to provide individually customized learning experiences.

[1583] System configuration

[1584] This system consists of three entities: the user, the terminal, and the server. The specific roles and operations of each entity are explained below.

[1585] User Registration and Authentication

[1586] A user accesses the educational platform's website or app and enters profile information such as name, email address, and password on the new registration screen. The device encrypts the entered information and sends it to the server via HTTPS. The server decrypts the received user information and stores it in a back-end SQL database (e.g., MySQL or PostgreSQL). The server then sends an email containing an authentication link to the user's email address. This authentication is performed using an email sending system such as SendGrid or Amazon SES. When the user clicks the link in the authentication email, the server verifies the token in the authentication link and updates the database to activate the account.

[1587] Customized educational content

[1588] After logging in, users enter their interests and learning goals on the profile settings page. The device encrypts this information and sends it to the server. The server then sends the received user information to an AI model (e.g., OpenAI's GPT-4) to generate an individually customized learning curriculum. This curriculum is sent to the device in JSON format, and the device displays it to the user.

[1589] Interactive learning support

[1590] When a user inputs a question or concern that arises during learning, the device sends the question to the server. The server sends the question to the AI ​​chatbot (generative AI model), which analyzes it in real time and generates an answer. The server then sends the generated answer to the device, which displays it to the user.

[1591] Example prompt sentence:

[1592] User: Teach me the basics of calculus.

[1593] AI Chatbot: Calculus is an important subject in high school mathematics. First of all, differentiation is the operation of finding the rate of change of a function. For example, the derivative of y = x^2 is dy / dx = 2x. On the other hand, integration is the operation of finding the cumulative amount of a function, and the integral of y = x^2 is ∫x^2 dx = (1 / 3)x^3 + C. Please let me know if there are any specific topics or problems you would like to know about.

[1594] Real-time support and feedback

[1595] The server schedules online sessions with experts or teachers based on the user's learning progress. The device displays a notification of the online session to the user and presents a session link at the specified time. The user clicks the link at the specified session time to interact with the expert or teacher in real time.

[1596] Progress management and evaluation

[1597] The device periodically sends the user's learning progress data (e.g., completed assignments, test results, and study time) to the server. The server records the received progress data in a database and performs data analysis. This analysis can be performed using Python tools such as Pandas or NumPy. The server generates a progress report based on the analysis results and sends it to the device. The device displays the progress report to the user, who can use it to plan their next learning steps.

[1598] Specific examples

[1599] For example, consider the case where a junior high school student, Person A, is working on a new mathematics topic, "Calculus." The user (Person A) registers and logs in after email authentication. Person A enters that he or she is interested in "Calculus" in his or her profile settings, and the server uses this information to generate an individually customized curriculum, which is sent to the device and displayed. If Person A enters a question while studying, such as "Teach me the basics of calculus," the server uses an AI model to instantly generate an answer and displays it on the device. The server also schedules an online session with an expert, with Person A interacting in real time at the specified time. The device sends Person A's learning progress data to the server, which generates a progress report and sends it to the device, where Person A can review the report and plan his or her next learning steps.

[1600] In this way, this system allows users to customize their learning experience and receive real-time expert support, making learning efficient and effective.

[1601] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1602] Step 1:

[1603] Users access the educational platform's website or app and enter profile information such as their name, email address, and password on the new registration screen.

[1604] Input: User profile information such as name, email address, and password.

[1605] Output: Encrypted user information.

[1606] What happens: A user fills out a form using a browser or app and clicks the "Register" button.

[1607] Step 2:

[1608] The terminal encrypts the entered information and sends it to the server via the HTTPS protocol.

[1609] Input: Profile information entered by the user.

[1610] Output: Encrypted user information sent to the server.

[1611] Specific operation: The terminal encrypts input data using SSL / TLS and sends an HTTPS request to the server.

[1612] Step 3:

[1613] The server decrypts the received user information and stores it in a back-end SQL database (e.g. MySQL or PostgreSQL).

[1614] Input: Encrypted user information.

[1615] Output: User information stored in the database.

[1616] Specific operation: The server decrypts the received data using SSL / TLS and inserts the user information into the database using an SQL query.

[1617] Step 4:

[1618] The server sends an email containing an authentication link to the user's email address. For example, SendGrid or Amazon SES is used as the email sending system.

[1619] Input: The user's email address.

[1620] Output: The authentication email sent to the user.

[1621] Specific operation: The server uses the email API to generate email content and send an authentication link to the specified email address.

[1622] Step 5:

[1623] The user checks their mailbox and clicks on the link in the verification email.

[1624] Input: The link in the verification email.

[1625] Output: The authentication request sent to the server.

[1626] What happens: The user opens the email and clicks on a link, causing the browser to send a request to the server.

[1627] Step 6:

[1628] The server validates the token in the authentication link and updates its database to validate the user account.

[1629] Input: Token for authentication link.

[1630] Output: Activated user account information.

[1631] What happens: The server validates the link's token and updates the user record in the database using an SQL query.

[1632] Step 7:

[1633] After logging in, users enter their interests and learning goals on the profile settings page.

[1634] Input: Information such as interests and learning goals.

[1635] Output: Encrypted learning objective information.

[1636] Specific behavior: A user logs in, enters information on a settings page, and clicks the save button.

[1637] Step 8:

[1638] The terminal encrypts this input information and sends it to the server.

[1639] Input: User-entered interest and learning goal information.

[1640] Output: Encrypted learning objective information sent to the server.

[1641] Specific operation: The terminal encrypts input data using SSL / TLS and sends an HTTPS request to the server.

[1642] Step 9:

[1643] The server sends the received user information to an AI model (e.g., OpenAI's GPT-4) to generate an individually customized learning curriculum.

[1644] Input: User's learning goals, profile information.

[1645] Output: The generated learning curriculum.

[1646] Specific operation: The server sends user information to the AI ​​model and generates a curriculum from the model's response.

[1647] Step 10:

[1648] The server sends the generated curriculum in JSON format to the terminal, which displays it to the user.

[1649] Input: The generated learning curriculum.

[1650] Output: The curriculum that is displayed to the user.

[1651] Specific operation: The server sends curriculum data in JSON format to the terminal, which parses it and displays it on the user interface.

[1652] Step 11:

[1653] When the user inputs any doubts or questions that arise during the study, the terminal sends this question to the server.

[1654] Input: User's doubt or question.

[1655] Output: The query data sent to the server.

[1656] Specific operation: The user enters a question and clicks the send button, causing the device to send the data to the server.

[1657] Step 12:

[1658] The server sends the question to the AI ​​model, which analyzes it and generates an answer in real time.

[1659] Input: The user's question.

[1660] Output: The generated answer.

[1661] How it works: The server passes a question to the AI ​​model and receives the answer generated by the model.

[1662] Step 13:

[1663] The server generates a response and sends it to the terminal, which displays it to the user.

[1664] Input: The generated answer.

[1665] Output: The answer that is displayed to the user.

[1666] Specific operation: The server sends the response data to the terminal, which parses it and displays it on the user interface.

[1667] Step 14:

[1668] The server schedules online sessions with experts and teachers based on the user's learning progress.

[1669] Input: User's learning progress data.

[1670] Output: Online session schedule.

[1671] Specific behavior: The server analyzes the progress data and reserves an online session at the appropriate time.

[1672] Step 15:

[1673] The terminal displays a notification of the online session to the user and presents the session link at the specified time.

[1674] Enter: Schedule an online session.

[1675] Output: The notification and session link that is displayed to the user.

[1676] Specific operation: The terminal receives the session schedule and displays a notification and link on the user interface.

[1677] Step 16:

[1678] Users click on the link at the designated session time to interact with the expert or teacher in real time.

[1679] Input: Online session link.

[1680] Output: Communication with experts and teachers.

[1681] What happens: The user clicks on a link and connects with an expert or teacher via a video conferencing platform or similar.

[1682] Step 17:

[1683] The terminal periodically transmits the user's learning progress data to the server.

[1684] Input: Learning progress data (e.g. completed assignments, test results, study time).

[1685] Output: Progress data sent to the server.

[1686] Specific operation: The device collects progress data at regular intervals, encrypts it, and sends it to the server.

[1687] Step 18:

[1688] The server records the received progress data in a database and performs data analysis.

[1689] Input: Progress data.

[1690] Output: Parsed data.

[1691] Specific operation: The server stores progress data in an SQL database and analyzes it using data analysis tools (e.g., Python's Pandas or NumPy).

[1692] Step 19:

[1693] The server generates a progress report based on the analysis results and sends it to the terminal.

[1694] Input: Analysis results.

[1695] Output: The generated progress report.

[1696] Specific operation: The server aggregates the analysis results, generates a progress report including text and graphs, and sends it to the device in JSON format.

[1697] Step 20:

[1698] The device displays a progress report to the user, who can use it to plan their next learning steps.

[1699] Input: Progress report.

[1700] Output: The report that is displayed to the user.

[1701] Specific operation: The device parses the received report data and displays it visually in the user interface. The user can then check the content and set their next learning goal or plan.

[1702] (Application example 1)

[1703] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1704] Traditional education platforms lack the flexibility to accommodate individual learning requirements. Furthermore, in-factory training lacks a way to accept questions in real time and provide immediate answers. Furthermore, the lack of an environment for direct interaction with experts and instructors during training often results in insufficient learning outcomes. This makes it particularly difficult to provide efficient training in a real-world work environment for new and existing employees.

[1705] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1706] In this invention, the server includes: means for a user to input individual profile information and learning goals; means for generating a learning curriculum based on the user information received by the server; means for transmitting the generated learning curriculum to the user's terminal and displaying it; means for the user to input questions that arise during learning and for the server to instantly generate answers using AI; means for the server to schedule online sessions with experts or instructors in real time; means for transmitting the user's learning progress data from the terminal to the server and for the server to generate progress reports; means for a robot incorporating AI functions to support the user's training and provide on-site work procedures; means for inputting training status and questions to the robot in real time using the terminal and for the robot to instantly respond; and means including a sensor for detecting the user's actions when operating equipment and providing feedback at appropriate times. This allows users to receive individually customized learning experiences, enabling efficient and effective learning through real-time question and answer sessions and dialogue with experts.

[1707] "User" refers to the entity that uses the educational platform, who sets individual learning goals and manages their learning progress.

[1708] "Profile information" refers collectively to personal identification information and study-related information entered by a user.

[1709] "Learning goal" refers to the learning objective or goal that a user wants to achieve.

[1710] "Device" refers to the device (e.g., smartphone, tablet, or computer) used by a User to access the Education Platform.

[1711] "Server" refers to the central processing unit that receives, processes and manages information from users.

[1712] "Learning Curriculum" refers to a set of learning content and plans generated based on a user's profile information and learning goals.

[1713] "AI" refers to artificial intelligence technology, which has the ability to analyze and generate information interactively.

[1714] "Real-time" refers to instantaneous processing and response.

[1715] An "expert" is an individual who has advanced knowledge or skills in a particular field.

[1716] "Instructor" refers to an individual whose role is to provide education and training to users.

[1717] "Online Session" means an interactive educational or training session conducted via the Internet.

[1718] "Progress Data" refers to data and information that indicates a user's learning or training progress.

[1719] "Progress Report" refers to a report summarizing and analyzing a user's learning progress.

[1720] A "robot" is an automated mechanical device that incorporates AI to support user training and learning.

[1721] A "work procedure" refers to a series of steps or methods for accomplishing a particular task.

[1722] A "sensor" refers to a device that detects physical variables (e.g., movement or position) and acquires them as data.

[1723] This invention is an educational platform system using robots with built-in AI functions, which provides individually customized learning experiences and streamlines training within factories. The system mainly consists of a server, terminals, and users. The details are explained below.

[1724] User Registration and Authentication

[1725] A user accesses the educational platform's website or app and enters profile information such as name, email address, and password on the new registration screen. The device sends the entered information to the server, which records it in a database. An email containing a verification link is sent to the user, and when the user clicks the link in the verification email, the account is activated.

[1726] Customized educational content

[1727] After logging in, users enter their interests and learning goals on a profile setting page. The device sends this information to the server, which then uses an AI model to generate an individually customized learning curriculum based on the received information. The generated curriculum is then sent to the device and displayed to the user.

[1728] Interactive learning support

[1729] When a user inputs a question or concern that arises during learning, the question is sent to the server via the device. The server uses an AI chatbot to instantly generate an answer and provides it to the user via the device in real time. If necessary, the question may be redirected to an expert.

[1730] Real-time support and feedback

[1731] The server schedules online sessions with experts or instructors based on the user's learning progress, etc. The device displays a notification of the online session to the user and presents a session link at the specified time. When the specified session time arrives, the user clicks the notification link to begin a real-time dialogue with the expert or instructor.

[1732] Progress management and evaluation

[1733] The device periodically sends the user's learning progress data (e.g., completed assignments, test results, study time) to the server. The server records the received progress data in a database and analyzes it. The server generates a progress report based on the analysis results and sends it to the device to display to the user. The user can use the report to plan their next learning steps.

[1734] Robotic training support

[1735] The robot, which incorporates AI functions, supports user training and provides guidance on on-site work procedures. Training status and questions are input to the robot in real time using a terminal, and the robot responds immediately. In addition, when the user operates equipment, the robot detects the user's movements using built-in sensors and provides feedback at the appropriate time.

[1736] Specific examples

[1737] For example, if a new employee needs to learn how to operate a new machine, the system works like this:

[1738] 1. A user (new employee) registers and logs in after completing email authentication.

[1739] 2. The user selects "Machine Operation" in their profile settings and enters their learning goals.

[1740] 3. Based on this information, the server generates a customized machine operation training program and displays it on the terminal.

[1741] 4. When a user enters a question during training, the server uses an AI chatbot to instantly generate an answer and display it on the device.

[1742] 5. The server schedules an online session with an expert, and the user joins the session and asks questions directly.

[1743] 6. Based on the user's progress data, the server generates a progress report and displays it to the user on the terminal.

[1744] 7. User reviews report and plans next learning steps.

[1745] 8. The robot guides the user through the work steps, uses sensors to detect movements and provides appropriate feedback.

[1746] Prompt Sentence Examples

[1747] "Please provide a method for designing an easy-to-use AI interactive robot trainer so that new employees can receive real-time answers to any questions they may have during training on new machine operation."

[1748] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1749] Step 1:

[1750] The user enters their profile information and learning goals, including their name, email address, password, interests, learning goals, etc. The device then sends this information to the server.

[1751] Step 2:

[1752] The server records the information in a user database based on the received user information, generates an email containing an authentication link, and sends it to the user. This allows the server to securely manage the user's profile information and start the authentication process.

[1753] Step 3:

[1754] When the user clicks on the link in the authentication email, the server activates the account, which causes the server to update the user's authentication status and grant access to the learning platform.

[1755] Step 4:

[1756] After logging in, users enter their interests and learning goals on the profile settings page. The device then sends this information back to the server, which then obtains the data needed to generate the most appropriate learning curriculum.

[1757] Step 5:

[1758] Based on the received information, the server uses an AI model to generate an individually customized learning curriculum, which includes learning content that reflects the user's interests and learning goals, and then sends the curriculum to the device and displays it to the user.

[1759] Step 6:

[1760] When a user enters a question or concern that arises during their study into their device, the question is sent to the server, which uses an AI chatbot to instantly generate an answer and send it to the device in real time, allowing users to immediately resolve any doubts they may have while studying.

[1761] Step 7:

[1762] The server periodically receives the user's learning progress data (e.g., completed assignments, test results, and study time). It analyzes the received data and generates a progress report. The generated progress report is sent to the terminal and displayed to the user.

[1763] Step 8:

[1764] The server schedules online sessions with experts or instructors as needed based on the user's learning progress, and the device displays a notification of the online session to the user and provides a session link at the specified time.

[1765] Step 9:

[1766] Once users click on the session link, an online session will begin, allowing for real-time interaction with experts and mentors, allowing users to directly ask questions about specific questions and issues and receive expert answers.

[1767] Step 10:

[1768] The AI-embedded robot guides users through work procedures and uses sensors to detect their movements. When users operate the equipment, the robot provides timely feedback, allowing users to receive effective training in a real-world work environment.

[1769] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1770] This invention relates to an educational platform that utilizes an AI conversational chatbot and emotion recognition engine, and describes how to specifically implement the system to provide a personalized learning experience.

[1771] System configuration

[1772] This system consists of four components: the user, the device, the server, and the emotion engine, which work together to realize education. It also integrates AI chatbots with support from experts and teachers.

[1773] User Registration and Authentication

[1774] 1. A user accesses the educational platform's website or app and enters profile information such as name, email address, and password on the new registration screen.

[1775] 2. The device sends the entered profile information to the server.

[1776] 3. The server stores the user information in a database based on the received profile information.

[1777] 4. The server sends an email containing a verification link to the user's email address.

[1778] 5. The user clicks the link in the verification email to activate their account.

[1779] 6. The server verifies that the user clicked the link and updates the account status to "active."

[1780] Customized educational content

[1781] 1. The user logs in and accesses the profile settings page.

[1782] 2. The user inputs their area of ​​interest or learning goal (e.g., mathematics, high school level, specifically calculus).

[1783] 3. The device sends the user's input information to the server.

[1784] 4. Based on the information received by the server, the AI ​​chatbot algorithm is run to generate a customized learning curriculum.

[1785] 5. The server sends the generated curriculum to the terminal.

[1786] 6. The device displays the curriculum to the user and provides a button to start learning.

[1787] Emotion recognition engine integration

[1788] 1. The emotion engine monitors the user's input, voice, and facial expressions in real time.

[1789] 2. The device sends the user's emotional state data to the emotion engine.

[1790] 3. The emotion engine analyzes the received data and estimates the user's emotional state (e.g., stress, satisfaction, fatigue).

[1791] 4. The server adjusts the learning curriculum and the AI ​​chatbot's responses based on the emotional data obtained from the emotion engine.

[1792] 5. The server optimizes the learning environment and support according to the user's emotional state.

[1793] Interactive learning support

[1794] 1. The user inputs a question or concern that arises during learning (e.g., "Teach me the basics of calculus").

[1795] 2. The device sends the user's question to the server.

[1796] 3. The server analyzes the question received by the AI ​​chatbot and generates an answer.

[1797] 4. The server sends the answer obtained from the AI ​​chatbot to the device.

[1798] 5. The device displays the answers to the user, and also provides a field for entering additional questions if desired.

[1799] Real-time support and feedback

[1800] 1. The server schedules online sessions with experts and teachers (based on the user's learning progress and schedule).

[1801] 2. The server sends a notification to the device containing the session date and time and a link.

[1802] 3. The device displays a notification of the online session to the user.

[1803] 4. The user clicks the session link from the notification at the specified time.

[1804] 5. The server starts the online session and the expert or teacher connects.

[1805] 6. Users can ask questions directly during the session and receive real-time feedback.

[1806] Progress management and evaluation

[1807] 1. The device periodically sends the user's learning progress data (completed assignments, test results, time passage, etc.) to the server.

[1808] 2. The server records the received progress data in a database.

[1809] 3. The server analyzes the progress data and evaluates trends and rate of progress.

[1810] 4. The server generates a progress report based on the user's learning progress.

[1811] 5. The server generates a progress report and sends it to the device.

[1812] 6. The device displays a progress report to the user and suggests next learning steps.

[1813] Specific Examples

[1814] For example, let's say a junior high school student, Mr. A, wants to study mathematics efficiently. In this case, the system works as follows:

[1815] 1. A user (Mr. A) registers and logs in after completing email authentication.

[1816] 2. User (A) selects "High School Mathematics" in the profile settings and enters his / her learning goals.

[1817] 3. The server generates a high school mathematics curriculum based on this information and displays it on the terminal.

[1818] 4. The emotion engine analyzes the user's (person A's) facial expressions and voice to identify their emotional state.

[1819] 5. If the server determines based on emotional data that A is not enjoying the learning experience, it will adjust the curriculum to improve A's interest in learning.

[1820] 6. While studying, a user (Mr. A) types a question: "Please teach me the basics of differential and integral calculus."

[1821] 7. The server uses an AI chatbot to instantly generate a response and display it on the device.

[1822] 8. The server schedules an online session with an expert, and the user (Person A) joins the session and asks questions directly.

[1823] 9. The device sends Mr. A's learning progress data to the server, and the server generates a progress report and sends it to the device.

[1824] 10. User (Person A) reviews the report and plans the next learning steps.

[1825] In this way, the system can provide an individually customized learning experience and realize an advanced educational environment that combines real-time learning support and emotion recognition.

[1826] The processing flow will be explained below.

[1827] Program processing steps

[1828] User Registration and Authentication

[1829] Step 1:

[1830] A user accesses the education platform's website or app and enters profile information such as name, email address, and password on the new registration screen.

[1831] Step 2:

[1832] The device transmits the entered profile information to the server.

[1833] Step 3:

[1834] The server stores user information in a database based on the received profile information.

[1835] Step 4:

[1836] The server sends an email containing a verification link to the user's email address.

[1837] Step 5:

[1838] The user clicks the link in the verification email to activate their account.

[1839] Step 6:

[1840] The server verifies that the user clicked the link and updates the account status to "active."

[1841] Customized educational content

[1842] Step 1:

[1843] User logs in and visits the profile settings page.

[1844] Step 2:

[1845] The user inputs their area of ​​interest or learning goal (e.g., mathematics, high school level, specifically calculus).

[1846] Step 3:

[1847] The terminal transmits the user's input information to the server.

[1848] Step 4:

[1849] Based on the information received by the server, the AI ​​chatbot's algorithm is run to generate a customized learning curriculum.

[1850] Step 5:

[1851] The server transmits the generated curriculum to the terminal.

[1852] Step 6:

[1853] The terminal displays the curriculum to the user and provides a button to start learning.

[1854] Emotion recognition engine integration

[1855] Step 1:

[1856] The emotion engine monitors the user's voice, facial expressions, and input in real time.

[1857] Step 2:

[1858] The terminal transmits the user's emotional state data to the emotion engine.

[1859] Step 3:

[1860] The emotion engine analyzes the received data and estimates the user's emotional state (e.g., stress, satisfaction, fatigue).

[1861] Step 4:

[1862] The server adjusts the learning curriculum and the responses of the AI ​​chatbot based on the emotional data obtained from the emotion engine.

[1863] Step 5:

[1864] The server optimizes the learning environment and support according to the user's emotional state.

[1865] Interactive learning support

[1866] Step 1:

[1867] The user inputs questions or doubts that arise during the study (e.g., "Please teach me the basics of calculus").

[1868] Step 2:

[1869] The terminal sends the user's question to the server.

[1870] Step 3:

[1871] The server analyzes the questions it receives and has the AI ​​chatbot generate answers.

[1872] Step 4:

[1873] The server sends the answer obtained from the AI ​​chatbot to the terminal.

[1874] Step 5:

[1875] The device displays the answers to the user and also provides a field where they can enter additional questions if desired.

[1876] Real-time support and feedback

[1877] Step 1:

[1878] The server schedules online sessions with experts and teachers (based on the user's learning progress and schedule).

[1879] Step 2:

[1880] The server sends a notification to the device containing the session date and time and a link.

[1881] Step 3:

[1882] The terminal displays a notification of the online session to the user.

[1883] Step 4:

[1884] The user clicks the session link from the notification at the specified time.

[1885] Step 5:

[1886] The server initiates the online session, and the expert or teacher connects.

[1887] Step 6:

[1888] Users can ask questions directly during the session and receive real-time feedback.

[1889] Progress management and evaluation

[1890] Step 1:

[1891] The device periodically sends the user's learning progress data (completed assignments, test results, study time) to the server.

[1892] Step 2:

[1893] The server records the received progress data in a database.

[1894] Step 3:

[1895] The server analyzes the progress data and evaluates trends and rate of progress.

[1896] Step 4:

[1897] The server generates a progress report based on the user's learning status.

[1898] Step 5:

[1899] The server generates a progress report and sends it to the device.

[1900] Step 6:

[1901] The device displays progress reports to the user and suggests next learning steps.

[1902] Specific examples

[1903] As a concrete example, let us consider the case where a junior high school student named A wants to study mathematics efficiently.

[1904] User Registration and Authentication

[1905] Step 1:

[1906] A user (Mr. A) registers and enters the necessary information.

[1907] Step 2:

[1908] The terminal sends this information to the server.

[1909] Step 3:

[1910] The server stores the information and sends a verification email.

[1911] Step 4:

[1912] The user (Mr. A) clicks on the link in the verification email to activate the account.

[1913] Customized educational content

[1914] Step 1:

[1915] The user (Mr. A) logs in and sets his / her learning interests and goals.

[1916] Step 2:

[1917] The terminal sends this information to the server.

[1918] Step 3:

[1919] The server generates a high school mathematics curriculum and transmits it to the terminal.

[1920] Step 4:

[1921] The device displays the learning curriculum and Person A begins learning.

[1922] Emotion recognition engine integration

[1923] Step 1:

[1924] The emotion engine analyzes Mr. A's facial expressions and voice to estimate his emotional state.

[1925] Step 2:

[1926] The device sends this data to the emotion engine.

[1927] Step 3:

[1928] The emotion engine sends the analysis results to the server.

[1929] Step 4:

[1930] The server adjusts learning content and feedback based on emotional data.

[1931] Interactive learning support

[1932] Step 1:

[1933] A user (person A) inputs a question such as "Teach me the basics of differential and integral calculus."

[1934] Step 2:

[1935] The terminal sends a question to the server.

[1936] Step 3:

[1937] The server analyzes the question using an AI chatbot and generates an answer.

[1938] Step 4:

[1939] The server sends the answer to the terminal and displays it to Mr. A.

[1940] Real-time support and feedback

[1941] Step 1:

[1942] The server schedules a session between A and the expert and sends a notification.

[1943] Step 2:

[1944] The terminal displays a notification of the session.

[1945] Step 3:

[1946] The user (person A) clicks on the session link and interacts with the expert.

[1947] Progress management and evaluation

[1948] Step 1:

[1949] The device periodically sends Mr. A's progress data to the server.

[1950] Step 2:

[1951] The server analyzes the data and generates a progress report.

[1952] Step 3:

[1953] The server sends the report to the device, and Person A plans his next learning step.

[1954] In this way, a system that integrates an emotion engine provides a personalized learning experience and real-time support.

[1955] Example 2

[1956] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1957] Current learning systems lack the ability to provide personalized learning experiences and real-time support. Furthermore, they often provide a uniform learning curriculum without considering the user's emotional state, which can lead to reduced learning efficiency and a loss of motivation. Furthermore, collaboration with experts and teachers is often not smooth, making it difficult to quickly solve problems. To address these issues, a comprehensive and efficient learning support system is needed.

[1958] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1959] In this invention, the server includes: a means for a user to input individual profile information and learning goals; a means for generating a learning curriculum based on the received user information; a means for transmitting the generated learning curriculum to the user's terminal and displaying it; a means for the user to input questions that arise during learning and for the server to instantly generate answers using AI; a means for the server to schedule online sessions with experts or teachers in real time; a means for transmitting the user's learning progress data from the terminal to the server and for the server to generate a progress report; a means for monitoring the user's facial expressions, input, and voice and analyzing the user's emotional state using an emotion recognition engine; and a means for the server to adjust the learning curriculum and the AI ​​chatbot's answers based on the analyzed emotional state. This makes it possible to provide users with a personalized learning experience and appropriate support, thereby improving learning efficiency.

[1960] "Profile Information" means the personal identification information and information regarding learning goals that a User provides when registering with the System.

[1961] A "learning curriculum" is a personalized learning plan generated by the server based on a user's profile information and learning goals.

[1962] A "terminal" is an electronic device such as a computer, smartphone, or tablet that allows a user to access and operate the system.

[1963] "Server" means a central processing system that receives, stores, and analyzes user profile information, and generates and transmits learning curriculum.

[1964] "AI" is an algorithm that uses artificial intelligence technology to analyze user input data and generate appropriate answers and support.

[1965] An "online session" is a session with video call or chat functionality that allows users to communicate with experts or teachers in real time.

[1966] "Study progress data" is information about a user's learning activities, including completed assignments, test results, study time, and the like.

[1967] An "emotion recognition engine" is software or algorithms that analyze a user's facial expressions, input, and voice to infer their emotional state.

[1968] "Real-time" is a time concept that means immediate or near-immediate data processing and response.

[1969] Hereinafter, embodiments of the present invention will be described in detail.

[1970] User Registration and Authentication

[1971] A user accesses the educational platform's website or app and enters profile information such as name, email address, and password on the new registration screen. The device sends the entered information to the server, which receives it and stores it in a database. After saving, the server sends an email containing a verification link to the user's email address. When the user clicks the verification link, the server updates the account status to "active."

[1972] Customized educational content

[1973] After logging in, the user enters their areas of interest and learning goals. The device sends the input information to the server, which then runs the AI ​​chatbot algorithm based on the received information. This algorithm uses TensorFlow or PyTorch to generate a customized learning curriculum. The generated curriculum is sent to the device and displayed on the user's screen.

[1974] Emotion recognition engine integration

[1975] The emotion recognition engine monitors the user's input, voice, and facial expressions in real time. Software such as OpenCV and TensorFlow is used to analyze data obtained from the webcam and microphone used by the user during learning. The device sends the acquired emotional data to the emotion recognition engine, which then sends the analyzed data to the server. The server analyzes the emotional data and adjusts the learning curriculum and the responses of the AI ​​chatbot.

[1976] Interactive learning support

[1977] When a user enters a question that arises during learning, the device sends the question to the server. The server receives the question and uses an AI chatbot to instantly generate an answer. The AI ​​chatbot used uses GPT-3 or BERT, and the generated answer is sent to the device and displayed to the user. A field is also provided where additional questions can be asked if necessary.

[1978] Real-time support and feedback

[1979] The server schedules online sessions with experts or teachers based on the user's learning progress and schedule. The date, time, and link of the scheduled session are sent to the device, and the user joins the online session via the notification. During the session, the user can ask questions directly and receive real-time feedback from the experts or teachers. Zoom or Google Meet is commonly used as the video conferencing system.

[1980] Progress management and evaluation

[1981] The device periodically sends the user's learning progress data to the server. The progress data includes completed assignments, test results, and study time. The server analyzes the received data and uses Python's Pandas and NumPy to evaluate trends and progress speed. After analysis, the server generates a progress report and sends it to the device. The device displays the progress report to the user and suggests the next learning step.

[1982] Specific examples

[1983] For example, if a junior high school student named A wants to efficiently improve their math studies, the system operates as follows: The user (A) registers and logs in after verifying their email address. They select "High School Mathematics" in their profile settings and enter their learning goals. The server generates a curriculum based on this information and displays it on their device. The emotion recognition engine analyzes A's facial expressions and voice to identify their emotional state. The server adjusts the curriculum based on the emotional data to increase their interest in learning. If the user types a question such as "Teach me the basics of calculus," the server uses an AI chatbot to generate an answer and displays it on their device. The server also schedules an online session with an expert, allowing the user to participate and ask questions directly. The device sends learning progress data to the server, which then generates a progress report and sends it to the device. The user reviews the report and plans their next learning steps. In this way, it is possible to provide individually customized learning experiences and real-time support.

[1984] Prompt Sentence Examples

[1985] "Generate a customized learning curriculum for high school mathematics calculus."

[1986] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1987] Step 1:

[1988] The user accesses the educational platform and enters their profile information (name, email address, password) on the new registration screen.

[1989] Input: Name, email address, and password provided by the user.

[1990] Output: New registration request.

[1991] Step 2:

[1992] The device transmits the entered profile information to the server.

[1993] Input: Profile information entered by the user.

[1994] Output: New registration request received on the server side.

[1995] Step 3:

[1996] The server stores the received profile information in a database and sends an email containing a verification link to the user's email address.

[1997] Input: Received profile information.

[1998] Data manipulation: Create a new user record in the database.

[1999] Output: Sending verification email.

[2000] Step 4:

[2001] The user clicks the link in the verification email to activate their account.

[2002] Input: Verification email.

[2003] Output: Authentication page accessed.

[2004] Step 5:

[2005] The server verifies that the user clicked the link and updates the account status to "active."

[2006] Input: Authentication link click information.

[2007] Data manipulation: Update the user status in the database.

[2008] Output: Account enabled.

[2009] Step 6:

[2010] Users log in and enter their interests and learning goals.

[2011] Input: User login information and learning goal (e.g., mathematics, high school level, specifically calculus).

[2012] Output: Learning goal setting request.

[2013] Step 7:

[2014] The terminal transmits the user's input information to the server.

[2015] Input: Learning objectives set by the user.

[2016] Output: Sends a learning goal setting request to the server.

[2017] Step 8:

[2018] Based on the information received by the server, the AI ​​chatbot's algorithm is run to generate a customized learning curriculum.

[2019] Input: User learning goals and AI algorithms (using TensorFlow or PyTorch).

[2020] Data Computing: Using generative AI models to build personalized learning curricula.

[2021] Output: A customized learning curriculum.

[2022] Step 9:

[2023] The server transmits the generated learning curriculum to the terminal.

[2024] Input: The generated learning curriculum.

[2025] Output: Send curriculum to device.

[2026] Step 10:

[2027] The terminal displays the learning curriculum to the user and provides a button to start learning.

[2028] Input: Learning curriculum received from the server.

[2029] Output: Display the curriculum on the learning screen and provide a button to start learning.

[2030] Step 11:

[2031] The emotion engine monitors the user's input, voice, and facial expressions in real time, and the device transmits that data.

[2032] Input: User facial expression, input, and voice data.

[2033] Data processing: Data extraction for sentiment analysis.

[2034] Output: Emotion data sent to the server.

[2035] Step 12:

[2036] The server analyzes the data obtained from the emotion engine and adjusts the learning curriculum and the responses of the AI ​​chatbot based on the user's emotional state.

[2037] Input: Parsed emotion data.

[2038] Data Computing: Aligning learning curriculum and AI chatbots.

[2039] Output: Generation of tailored curriculum and response content.

[2040] Step 13:

[2041] When a user inputs a question that arises during learning, the terminal sends the question to the server.

[2042] Input: A question from the user.

[2043] Output: Sends a query to the server.

[2044] Step 14:

[2045] The server analyzes the questions it receives and has the AI ​​chatbot generate answers.

[2046] Input: The question received.

[2047] Data Computation: Generate answers using generative AI models (such as GPT-3 or BERT).

[2048] Output: The generated answer.

[2049] Step 15:

[2050] The server sends the generated answer to the terminal, which displays it to the user.

[2051] Input: The generated answer.

[2052] Output: Send and display the answer to the terminal.

[2053] Step 16:

[2054] The server schedules online sessions with experts and teachers and sends the session date, time and link to the device.

[2055] Input: User's learning progress data.

[2056] Data calculation: Session scheduling at the right time.

[2057] Output: Sending session notifications.

[2058] Step 17:

[2059] The terminal displays a notification of the online session to the user, and the user clicks on the session link from the notification at the specified time.

[2060] Input: The session notification received from the server.

[2061] Output: Display a notification and provide a link.

[2062] Step 18:

[2063] The server initiates the online session, allowing users to ask questions to the teacher and receive real-time feedback.

[2064] Input: User questions and teacher feedback.

[2065] Output: Real-time Q&A.

[2066] Step 19:

[2067] The terminal transmits the user's learning progress data to the server, which generates a progress report.

[2068] Input: Learning progress data.

[2069] Data Calculation: Analyze progress data using Python's Pandas and NumPy.

[2070] Output: Generates a progress report.

[2071] Step 20:

[2072] The server generates a progress report and sends it to the terminal, which displays it to the user and suggests the next learning step.

[2073] Input: The generated progress report.

[2074] Output: Report sent to terminal and displayed, suggesting next steps.

[2075] (Application example 2)

[2076] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[2077] Conventional educational platforms and training systems struggle to provide individually customized learning experiences, particularly in providing appropriate learning support in real time based on the learner's emotional state. They also lack the ability to instantly connect with experts and educators, and require flexible responses based on the learner's progress. This can lead to learners being unable to progress efficiently, resulting in a decline in the quality of their learning.

[2078] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for a user to input individual profile information and learning goals; means for generating a learning curriculum based on the user information received by the server; means for transmitting the generated learning curriculum to the user's terminal and displaying it; means for the user to input questions that arise during learning and for the server to instantly generate answers using AI; means for the server to schedule online sessions with experts and educators in real time; means for transmitting the user's learning progress data from the terminal to the server and for the server to generate a progress report; means for the server to analyze the user's emotional state and adjust the learning curriculum based on the emotional data; means for estimating the user's emotions using an emotion recognition engine; and means for the AI ​​chatbot to adjust the dialogue according to the user's emotional state. This provides an individually customized learning experience that takes the user's emotional state into consideration, enabling real-time support and appropriate adjustment of the learning curriculum.

[2079] 1. "User" means an individual or organization that uses the educational platform to carry out learning activities.

[2080] 2. "Profile Information" refers to individual information entered by a user, such as name, email address, and learning goals.

[2081] 3. A "learning curriculum" is a set of learning plans and content generated based on a user's learning goals.

[2082] 4. "Server" is a computer system that processes requests from users, generates learning curricula, and manages progress data.

[2083] 5. "Terminal" means a device through which a User accesses the educational platform and uses the learning curriculum.

[2084] 6. An "AI chatbot" is a program that uses artificial intelligence to generate instant answers to user questions.

[2085] 7. An "emotion recognition engine" is a technology that analyzes a user's facial expressions and voice data to estimate their emotional state.

[2086] 8. "Emotions" refers to the user's psychological state during learning, such as stress, satisfaction, fatigue, etc.

[2087] 9. An "expert" is a person with advanced knowledge and experience in a particular field who provides guidance and support to users.

[2088] 10. "Online Session" means a form of support provided via video call or chat in real time with an expert or educator via a server.

[2089] 11. "Progress Data" means data that indicates a User's learning progress, including completed assignments and test results.

[2090] 12. "Progress Report" means a report of a User's learning status generated based on the Progress Data.

[2091] System configuration

[2092] This embodiment of the system consists of a user, a terminal, a server, and an emotion recognition engine. The server performs the main processing and interacts with the user through the terminal. The server provides an educational platform, generating individualized programs, managing study goals, answering questions, and providing emotion-based support.

[2093] User Registration and Authentication

[2094] 1. A user accesses the educational platform and enters profile information such as name, email address, and password.

[2095] 2. The device sends this profile information to the server, which stores it in a database and sends a verification email to the user's email address. The user clicks on the link in the email to activate their account.

[2096] Customized educational content

[2097] 1. After logging in, the user enters their areas of interest and learning goals.

[2098] 2. The device sends the user's input information to the server, which then uses the AI ​​chatbot's algorithm to generate a customized learning curriculum, which is then sent to the device and displayed to the user.

[2099] Emotion recognition engine integration

[2100] 1. The emotion recognition engine monitors the user's facial expressions and voice data in real time.

[2101] 2. The device sends the user's emotional data to the emotion recognition engine, which then provides the analysis results to the server.

[2102] 3. The server adjusts the learning curriculum and the AI ​​chatbot's responses based on the emotional data.

[2103] Interactive learning support

[2104] 1. The user types in a question while studying.

[2105] 2. The device sends the question to the server, where the AI ​​chatbot analyzes it and generates an answer, which is then sent to the device and displayed to the user.

[2106] Real-time support and feedback

[2107] 1. The server schedules an online session with an expert or educator. A notification of the session is sent to the user's device and displayed. The online session starts at the specified time, allowing the user to receive real-time support.

[2108] Progress management and evaluation

[2109] 1. The device periodically sends the user's learning progress data to the server. The server analyzes the received data and generates a progress report. The report is then sent to the device and displayed to the user.

[2110] Specific examples

[2111] For example, consider a new employee undergoing work training in a factory. Using this system, the new employee inputs the necessary information and is provided with a curriculum that includes the proper work procedures. Employee emotions are also monitored, and if stress or confusion is detected, an AI chatbot will provide appropriate support.

[2112] Example prompt sentence:

[2113] "Are you ready to take the next step? Answer 'yes' or 'no'."

[2114] Step 1: Gather your tools

[2115] "AI Chatbot: My emotional state is stressed. How can I help?"

[2116] The system combines an individually tailored learning experience with real-time support, enabling learners to learn efficiently and effectively.

[2117] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2118] Step 1:

[2119] A user accesses the educational platform and enters their individual profile information (such as name, email address, and password). This information is sent to the server via their device. The server receives the information, stores it in a database, and sends the user an email containing an authentication link.

[2120] Input: Profile information entered by the user

[2121] Output: Send authentication email, save user information to database

[2122] Operation: The server performs the function of generating and sending an authentication email.

[2123] Step 2:

[2124] The user clicks on the link in the verification email they received to activate their account. The server confirms this action and updates the account status to "Active."

[2125] Input: User clicks authentication link

[2126] Output: Account status update

[2127] Behavior: The server updates the account status when the user clicks the authentication link.

[2128] Step 3:

[2129] The user logs in and enters their areas of interest and learning goals. The device sends this information to the server, which then uses the AI ​​chatbot's algorithm to generate a personalized curriculum. The generated curriculum is then sent to the device and displayed to the user.

[2130] Input: User interests and learning goals

[2131] Output: Display of generated learning curriculum

[2132] How it works: The server uses an AI chatbot to generate a learning curriculum and send it to the device.

[2133] Step 4:

[2134] The emotion recognition engine monitors the user's facial expressions and voice in real time, and the emotion data is sent from the device to the server, which then analyzes the data to identify the user's emotional state.

[2135] Input: User's facial expressions and voice data

[2136] Output: Identification of emotional state (e.g., stress, satisfaction, fatigue)

[2137] How it works: The emotion recognition engine analyzes the data and infers the emotional state.

[2138] Step 5:

[2139] The server adjusts the learning curriculum and the AI ​​chatbot's responses based on the emotional data, optimizing the curriculum to make learning more enjoyable for users depending on their emotional state.

[2140] Input: Parsed emotion data

[2141] Output: Tailored learning curriculum and AI chatbot answers

[2142] How it works: The server uses generative AI models to tailor content and dialogue based on emotion data.

[2143] Step 6:

[2144] The user enters a question that arises during the learning process, and the device sends the question to the server, which uses an AI chatbot to instantly generate an answer, which is then sent to the device and displayed to the user.

[2145] Input: User question

[2146] Output: Answer by AI chatbot

[2147] How it works: The server analyzes the question, generates an appropriate answer, and sends it to the device.

[2148] Step 7:

[2149] The server schedules online sessions with experts and educators. Session notifications are sent to the device and displayed to the user. The user joins the session at the designated time and receives real-time feedback.

[2150] Input: User's learning progress and schedule

[2151] Output: Online session schedule and notifications

[2152] How it works: The server manages the schedule and sends notifications.

[2153] Step 8:

[2154] The device periodically sends the user's learning progress data to the server, which analyzes the progress data and generates a progress report, which is sent to the device and displayed to the user.

[2155] Input: Learning progress data

[2156] Output: Progress report

[2157] How it works: The server analyzes the progress data and generates a report.

[2158] This allows users to receive a personalized learning experience, with real-time support and an optimized curriculum.

[2159] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[2160] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2161] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[2162] [Fourth embodiment]

[2163] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[2164] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[2165] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[2166] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[2167] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[2168] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[2169] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[2170] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[2171] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[2172] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[2173] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[2174] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[2175] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2176] This invention relates to an educational platform that utilizes AI interactive chatbots, and describes specific implementation methods for the system to provide individually customized learning experiences.

[2177] System configuration

[2178] This system consists of three components: the user, the device, and the server, and these components work together to realize education. It also integrates AI chatbots with support from experts and teachers.

[2179] User Registration and Authentication

[2180] 1. The user accesses the educational platform's website or app and enters profile information such as name, email address, and password on the new registration screen.

[2181] 2. The terminal sends the entered information to the server.

[2182] 3. The server uses this information to record the user information in its database and sends the user an email containing an authentication link.

[2183] 4. When the user clicks on the link in the verification email, the account is activated on the server side.

[2184] Customized educational content

[2185] 1. After logging in, users enter their interests and learning goals into the profile settings page.

[2186] 2. The terminal sends this input information to the server.

[2187] 3. Based on the received information, the server uses an AI chatbot to generate an individually customized learning curriculum.

[2188] 4. The server sends the generated curriculum to the terminal, where it is displayed to the user.

[2189] Interactive learning support

[2190] 1. When a user has a question or concern that arises during their study, they send the question to the server via their terminal.

[2191] 2. The server analyzes the received question using an AI chatbot and instantly generates an answer.

[2192] 3. The server sends the generated answer to the device, providing the user with a real-time answer, and may redirect the question to an expert if necessary.

[2193] Real-time support and feedback

[2194] 1. The server schedules online sessions with experts and teachers based on the user's learning progress, etc.

[2195] 2. The device displays a notification of the online session to the user and provides the session link at the specified time.

[2196] 3. When the designated session time arrives, the user clicks on the notification link to begin a real-time conversation with the expert or teacher.

[2197] Progress management and evaluation

[2198] 1. The device periodically sends the user's learning progress data (e.g., completed assignments, test results, study time) to the server.

[2199] 2. The server records the received progress data in a database and analyzes it.

[2200] 3. The server generates a progress report based on the analysis results and sends it to the device.

[2201] 4. The device displays a progress report to the user, who can use the report to plan their next learning steps.

[2202] Specific Examples

[2203] For example, let's say a junior high school student, Mr. A, wants to study mathematics efficiently. In this case, the system works as follows:

[2204] 1. A user (Mr. A) registers and logs in after completing email authentication.

[2205] 2. User (A) selects "High School Mathematics" in the profile settings and enters his / her learning goals.

[2206] 3. The server generates a high school mathematics curriculum based on this information and displays it on the terminal.

[2207] 4. While studying, a user (Mr. A) types a question: "Please teach me the basics of differential and integral calculus."

[2208] 5. The server uses an AI chatbot to instantly generate a response and display it on the device.

[2209] 6. The server schedules an online session with an expert, and the user (Person A) joins the session and asks questions directly.

[2210] 7. The device sends Mr. A's learning progress data to the server, and the server generates a progress report and sends it to the device.

[2211] 8. User (A) reviews the report and plans the next learning steps.

[2212] In this way, the system provides an individually customized learning experience, enabling efficient and effective learning with the support of experts.

[2213] The processing flow will be explained below.

[2214] Program processing steps

[2215] User Registration and Authentication

[2216] Step 1:

[2217] A user accesses the education platform's website or app and enters profile information such as name, email address, and password on the new registration screen.

[2218] Step 2:

[2219] The device transmits the entered profile information to the server.

[2220] Step 3:

[2221] The server stores user information in a database based on the received profile information.

[2222] Step 4:

[2223] The server sends an email containing a verification link to the user's email address.

[2224] Step 5:

[2225] The user clicks the link in the verification email to activate their account.

[2226] Step 6:

[2227] The server verifies that the user clicked the link and updates the account status to "active."

[2228] Customized educational content

[2229] Step 1:

[2230] User logs in and visits the profile settings page.

[2231] Step 2:

[2232] The user inputs their area of ​​interest or learning goal (e.g., mathematics, high school level, specifically calculus).

[2233] Step 3:

[2234] The terminal transmits the user's input information to the server.

[2235] Step 4:

[2236] Based on the information received by the server, the AI ​​chatbot's algorithm is run to generate a customized learning curriculum.

[2237] Step 5:

[2238] The server transmits the generated curriculum to the terminal.

[2239] Step 6:

[2240] The terminal displays the curriculum to the user and provides a button to start learning.

[2241] Interactive learning support

[2242] Step 1:

[2243] The user inputs questions or doubts that arise during the study (e.g., "Please teach me the basics of calculus").

[2244] Step 2:

[2245] The terminal sends the user's question to the server.

[2246] Step 3:

[2247] The server analyzes the questions it receives and has the AI ​​chatbot generate answers.

[2248] Step 4:

[2249] The server sends the answer obtained from the AI ​​chatbot to the terminal.

[2250] Step 5:

[2251] The device displays the answers to the user and also provides a field where they can enter additional questions if desired.

[2252] Real-time support and feedback

[2253] Step 1:

[2254] The server schedules online sessions with experts and teachers (based on the user's learning progress and schedule).

[2255] Step 2:

[2256] The server sends a notification to the device containing the session date and time and a link.

[2257] Step 3:

[2258] The terminal displays a notification of the online session to the user.

[2259] Step 4:

[2260] The user clicks the session link from the notification at the specified time.

[2261] Step 5:

[2262] The server initiates the online session, and the expert or teacher connects.

[2263] Step 6:

[2264] Users can ask questions directly during the session and receive real-time feedback.

[2265] Progress management and evaluation

[2266] Step 1:

[2267] The device periodically sends the user's learning progress data (completed assignments, test results, time elapsed, etc.) to the server.

[2268] Step 2:

[2269] The server records the received progress data in a database.

[2270] Step 3:

[2271] The server analyzes the progress data and evaluates trends and rate of progress.

[2272] Step 4:

[2273] The server generates a progress report based on the user's learning status.

[2274] Step 5:

[2275] The server generates a progress report and sends it to the device.

[2276] Step 6:

[2277] The device displays progress reports to the user and suggests next learning steps.

[2278] Example 1

[2279] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2280] Traditional educational platforms lack the ability to customize content to meet individual learning needs and goals, making it difficult for users to learn efficiently and effectively. Furthermore, the mechanisms for providing real-time support from experts and teachers are incomplete, limiting the means by which users can get immediate answers to questions that arise during their studies. Progress management and assessment must also be done manually, placing a burden on users.

[2281] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[2282] In this invention, the server includes: means for a user to input individual profile information and learning goals; means for the terminal to encrypt the input information and transmit it to the server; means for generating an individually customized learning curriculum based on the user information received by the server; means for transmitting the generated learning curriculum to the user's terminal and displaying it; means for the user to input questions that arise during learning and for the terminal to transmit the questions to the server; means for the server to instantly generate answers to the questions received by the server using an AI model; means for the server to schedule online sessions with experts or teachers in real time; means for the terminal to display notifications of the online sessions to the user; means for the terminal to transmit the user's learning progress data to the server; means for the server to analyze the received learning progress data and generate a progress report; and means for the terminal to transmit the generated progress report to the terminal and display it to the user. This provides a customized learning experience that meets the user's individual learning needs, enables real-time question resolution and direct communication with experts, and automates progress management and evaluation, thereby enabling efficient and effective learning for the user.

[2283] "User" refers to an individual who uses the educational platform and who enters individual profile information and learning goals.

[2284] "Terminal" refers to a device such as a PC or smartphone, which is a means for sending information from the user to the server and receiving and displaying information from the server.

[2285] The "server" is a computer system that controls the entire system, including generating a learning curriculum based on received user information, answering user questions, and analyzing progress data.

[2286] "Profile Information" means personal identification information such as name, email address, and password that a User enters when registering on the Education Platform.

[2287] "Learning goals" refer to the specific learning outcomes or objectives that a user wishes to achieve, and serve as the basis for the system to generate a customized learning curriculum.

[2288] "Learning curriculum" refers to an individual learning schedule and learning content generated based on a user's profile information and learning goals.

[2289] A "question" is something that a user inputs when they are unsure about something they are unsure about while studying, and is something that requires an answer.

[2290] An "AI model" refers to an algorithm or system that uses artificial intelligence technology to analyze data and generate answers to user questions.

[2291] An "expert" refers to an individual or occupation that has advanced knowledge and experience in a specific field of study and provides expert answers to users' questions and inquiries.

[2292] "Online Session" refers to an opportunity for interaction and instruction with an expert or teacher conducted in real time via the Internet.

[2293] "Notifications" means information sent by the System to Users, including schedules for online sessions and important updates.

[2294] "Study progress data" is data that indicates how far a user has progressed in their studies, and includes information such as completed assignments, test results, and study time.

[2295] A "progress report" is a report summarizing the results of an analysis of a user's learning progress data, and serves as reference material when the user makes future learning plans.

[2296] This invention relates to an educational platform that utilizes AI interactive chatbots, and describes specific implementation methods for the system to provide individually customized learning experiences.

[2297] System configuration

[2298] This system consists of three entities: the user, the terminal, and the server. The specific roles and operations of each entity are explained below.

[2299] User Registration and Authentication

[2300] A user accesses the educational platform's website or app and enters profile information such as name, email address, and password on the new registration screen. The device encrypts the entered information and sends it to the server via HTTPS. The server decrypts the received user information and stores it in a back-end SQL database (e.g., MySQL or PostgreSQL). The server then sends an email containing an authentication link to the user's email address. This authentication is performed using an email sending system such as SendGrid or Amazon SES. When the user clicks the link in the authentication email, the server verifies the token in the authentication link and updates the database to activate the account.

[2301] Customized educational content

[2302] After logging in, users enter their interests and learning goals on the profile settings page. The device encrypts this information and sends it to the server. The server then sends the received user information to an AI model (e.g., OpenAI's GPT-4) to generate an individually customized learning curriculum. This curriculum is sent to the device in JSON format, and the device displays it to the user.

[2303] Interactive learning support

[2304] When a user inputs a question or concern that arises during learning, the device sends the question to the server. The server sends the question to the AI ​​chatbot (generative AI model), which analyzes it in real time and generates an answer. The server then sends the generated answer to the device, which displays it to the user.

[2305] Example prompt sentence:

[2306] User: Teach me the basics of calculus.

[2307] AI Chatbot: Calculus is an important subject in high school mathematics. First of all, differentiation is the operation of finding the rate of change of a function. For example, the derivative of y = x^2 is dy / dx = 2x. On the other hand, integration is the operation of finding the cumulative amount of a function, and the integral of y = x^2 is ∫x^2 dx = (1 / 3)x^3 + C. Please let me know if there are any specific topics or problems you would like to know about.

[2308] Real-time support and feedback

[2309] The server schedules online sessions with experts or teachers based on the user's learning progress. The device displays a notification of the online session to the user and presents a session link at the specified time. The user clicks the link at the specified session time to interact with the expert or teacher in real time.

[2310] Progress management and evaluation

[2311] The device periodically sends the user's learning progress data (e.g., completed assignments, test results, and study time) to the server. The server records the received progress data in a database and performs data analysis. This analysis can be performed using Python tools such as Pandas or NumPy. The server generates a progress report based on the analysis results and sends it to the device. The device displays the progress report to the user, who can use it to plan their next learning steps.

[2312] Specific examples

[2313] For example, consider the case where a junior high school student, Person A, is working on a new mathematics topic, "Calculus." The user (Person A) registers and logs in after email authentication. Person A enters that he or she is interested in "Calculus" in his or her profile settings, and the server uses this information to generate an individually customized curriculum, which is sent to the device and displayed. If Person A enters a question while studying, such as "Teach me the basics of calculus," the server uses an AI model to instantly generate an answer and displays it on the device. The server also schedules an online session with an expert, with Person A interacting in real time at the specified time. The device sends Person A's learning progress data to the server, which generates a progress report and sends it to the device, where Person A can review the report and plan his or her next learning steps.

[2314] In this way, this system allows users to customize their learning experience and receive real-time expert support, making learning efficient and effective.

[2315] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2316] Step 1:

[2317] Users access the educational platform's website or app and enter profile information such as their name, email address, and password on the new registration screen.

[2318] Input: User profile information such as name, email address, and password.

[2319] Output: Encrypted user information.

[2320] What happens: A user fills out a form using a browser or app and clicks the "Register" button.

[2321] Step 2:

[2322] The terminal encrypts the entered information and sends it to the server via the HTTPS protocol.

[2323] Input: Profile information entered by the user.

[2324] Output: Encrypted user information sent to the server.

[2325] Specific operation: The terminal encrypts input data using SSL / TLS and sends an HTTPS request to the server.

[2326] Step 3:

[2327] The server decrypts the received user information and stores it in a back-end SQL database (e.g. MySQL or PostgreSQL).

[2328] Input: Encrypted user information.

[2329] Output: User information stored in the database.

[2330] Specific operation: The server decrypts the received data using SSL / TLS and inserts the user information into the database using an SQL query.

[2331] Step 4:

[2332] The server sends an email containing an authentication link to the user's email address. For example, SendGrid or Amazon SES is used as the email sending system.

[2333] Input: The user's email address.

[2334] Output: The authentication email sent to the user.

[2335] Specific operation: The server uses the email API to generate email content and send an authentication link to the specified email address.

[2336] Step 5:

[2337] The user checks their mailbox and clicks on the link in the verification email.

[2338] Input: The link in the verification email.

[2339] Output: The authentication request sent to the server.

[2340] What happens: The user opens the email and clicks on a link, causing the browser to send a request to the server.

[2341] Step 6:

[2342] The server validates the token in the authentication link and updates its database to validate the user account.

[2343] Input: Token for authentication link.

[2344] Output: Activated user account information.

[2345] What happens: The server validates the link's token and updates the user record in the database using an SQL query.

[2346] Step 7:

[2347] After logging in, users enter their interests and learning goals on the profile settings page.

[2348] Input: Information such as interests and learning goals.

[2349] Output: Encrypted learning objective information.

[2350] Specific behavior: A user logs in, enters information on a settings page, and clicks the save button.

[2351] Step 8:

[2352] The terminal encrypts this input information and sends it to the server.

[2353] Input: User-entered interest and learning goal information.

[2354] Output: Encrypted learning objective information sent to the server.

[2355] Specific operation: The terminal encrypts input data using SSL / TLS and sends an HTTPS request to the server.

[2356] Step 9:

[2357] The server sends the received user information to an AI model (e.g., OpenAI's GPT-4) to generate an individually customized learning curriculum.

[2358] Input: User's learning goals, profile information.

[2359] Output: The generated learning curriculum.

[2360] Specific operation: The server sends user information to the AI ​​model and generates a curriculum from the model's response.

[2361] Step 10:

[2362] The server sends the generated curriculum in JSON format to the terminal, which displays it to the user.

[2363] Input: The generated learning curriculum.

[2364] Output: The curriculum that is displayed to the user.

[2365] Specific operation: The server sends curriculum data in JSON format to the terminal, which parses it and displays it on the user interface.

[2366] Step 11:

[2367] When the user inputs any doubts or questions that arise during the study, the terminal sends this question to the server.

[2368] Input: User's doubt or question.

[2369] Output: The query data sent to the server.

[2370] Specific operation: The user enters a question and clicks the send button, causing the device to send the data to the server.

[2371] Step 12:

[2372] The server sends the question to the AI ​​model, which analyzes it and generates an answer in real time.

[2373] Input: The user's question.

[2374] Output: The generated answer.

[2375] How it works: The server passes a question to the AI ​​model and receives the answer generated by the model.

[2376] Step 13:

[2377] The server generates a response and sends it to the terminal, which displays it to the user.

[2378] Input: The generated answer.

[2379] Output: The answer that is displayed to the user.

[2380] Specific operation: The server sends the response data to the terminal, which parses it and displays it on the user interface.

[2381] Step 14:

[2382] The server schedules online sessions with experts and teachers based on the user's learning progress.

[2383] Input: User's learning progress data.

[2384] Output: Online session schedule.

[2385] Specific behavior: The server analyzes the progress data and reserves an online session at the appropriate time.

[2386] Step 15:

[2387] The terminal displays a notification of the online session to the user and presents the session link at the specified time.

[2388] Enter: Schedule an online session.

[2389] Output: The notification and session link that is displayed to the user.

[2390] Specific operation: The terminal receives the session schedule and displays a notification and link on the user interface.

[2391] Step 16:

[2392] Users click on the link at the designated session time to interact with the expert or teacher in real time.

[2393] Input: Online session link.

[2394] Output: Communication with experts and teachers.

[2395] What happens: The user clicks on a link and connects with an expert or teacher via a video conferencing platform or similar.

[2396] Step 17:

[2397] The terminal periodically transmits the user's learning progress data to the server.

[2398] Input: Learning progress data (e.g. completed assignments, test results, study time).

[2399] Output: Progress data sent to the server.

[2400] Specific operation: The device collects progress data at regular intervals, encrypts it, and sends it to the server.

[2401] Step 18:

[2402] The server records the received progress data in a database and performs data analysis.

[2403] Input: Progress data.

[2404] Output: Parsed data.

[2405] Specific operation: The server stores progress data in an SQL database and analyzes it using data analysis tools (e.g., Python's Pandas or NumPy).

[2406] Step 19:

[2407] The server generates a progress report based on the analysis results and sends it to the terminal.

[2408] Input: Analysis results.

[2409] Output: The generated progress report.

[2410] Specific operation: The server aggregates the analysis results, generates a progress report including text and graphs, and sends it to the device in JSON format.

[2411] Step 20:

[2412] The device displays a progress report to the user, who can use it to plan their next learning steps.

[2413] Input: Progress report.

[2414] Output: The report that is displayed to the user.

[2415] Specific operation: The device parses the received report data and displays it visually in the user interface. The user can then check the content and set their next learning goal or plan.

[2416] (Application example 1)

[2417] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2418] Traditional education platforms lack the flexibility to accommodate individual learning requirements. Furthermore, in-factory training lacks a way to accept questions in real time and provide immediate answers. Furthermore, the lack of an environment for direct interaction with experts and instructors during training often results in insufficient learning outcomes. This makes it particularly difficult to provide efficient training in a real-world work environment for new and existing employees.

[2419] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[2420] In this invention, the server includes: means for a user to input individual profile information and learning goals; means for generating a learning curriculum based on the user information received by the server; means for transmitting the generated learning curriculum to the user's terminal and displaying it; means for the user to input questions that arise during learning and for the server to instantly generate answers using AI; means for the server to schedule online sessions with experts or instructors in real time; means for transmitting the user's learning progress data from the terminal to the server and for the server to generate progress reports; means for a robot incorporating AI functions to support the user's training and provide on-site work procedures; means for inputting training status and questions to the robot in real time using the terminal and for the robot to instantly respond; and means including a sensor for detecting the user's actions when operating equipment and providing feedback at appropriate times. This allows users to receive individually customized learning experiences, enabling efficient and effective learning through real-time question and answer sessions and dialogue with experts.

[2421] "User" refers to the entity that uses the educational platform, who sets individual learning goals and manages their learning progress.

[2422] "Profile information" refers collectively to personal identification information and study-related information entered by a user.

[2423] "Learning goal" refers to the learning objective or goal that a user wants to achieve.

[2424] "Device" refers to the device (e.g., smartphone, tablet, or computer) used by a User to access the Education Platform.

[2425] "Server" refers to the central processing unit that receives, processes and manages information from users.

[2426] "Learning Curriculum" refers to a set of learning content and plans generated based on a user's profile information and learning goals.

[2427] "AI" refers to artificial intelligence technology, which has the ability to analyze and generate information interactively.

[2428] "Real-time" refers to instantaneous processing and response.

[2429] An "expert" is an individual who has advanced knowledge or skills in a particular field.

[2430] "Instructor" refers to an individual whose role is to provide education and training to users.

[2431] "Online Session" means an interactive educational or training session conducted via the Internet.

[2432] "Progress Data" refers to data and information that indicates a user's learning or training progress.

[2433] "Progress Report" refers to a report summarizing and analyzing a user's learning progress.

[2434] A "robot" is an automated mechanical device that incorporates AI to support user training and learning.

[2435] A "work procedure" refers to a series of steps or methods for accomplishing a particular task.

[2436] A "sensor" refers to a device that detects physical variables (e.g., movement or position) and acquires them as data.

[2437] This invention is an educational platform system using robots with built-in AI functions, which provides individually customized learning experiences and streamlines training within factories. The system mainly consists of a server, terminals, and users. The details are explained below.

[2438] User Registration and Authentication

[2439] A user accesses the educational platform's website or app and enters profile information such as name, email address, and password on the new registration screen. The device sends the entered information to the server, which records it in a database. An email containing a verification link is sent to the user, and when the user clicks the link in the verification email, the account is activated.

[2440] Customized educational content

[2441] After logging in, users enter their interests and learning goals on a profile setting page. The device sends this information to the server, which then uses an AI model to generate an individually customized learning curriculum based on the received information. The generated curriculum is then sent to the device and displayed to the user.

[2442] Interactive learning support

[2443] When a user inputs a question or concern that arises during learning, the question is sent to the server via the device. The server uses an AI chatbot to instantly generate an answer and provides it to the user via the device in real time. If necessary, the question may be redirected to an expert.

[2444] Real-time support and feedback

[2445] The server schedules online sessions with experts or instructors based on the user's learning progress, etc. The device displays a notification of the online session to the user and presents a session link at the specified time. When the specified session time arrives, the user clicks the notification link to begin a real-time dialogue with the expert or instructor.

[2446] Progress management and evaluation

[2447] The device periodically sends the user's learning progress data (e.g., completed assignments, test results, study time) to the server. The server records the received progress data in a database and analyzes it. The server generates a progress report based on the analysis results and sends it to the device to display to the user. The user can use the report to plan their next learning steps.

[2448] Robotic training support

[2449] The robot, which incorporates AI functions, supports user training and provides guidance on on-site work procedures. Training status and questions are input to the robot in real time using a terminal, and the robot responds immediately. In addition, when the user operates equipment, the robot detects the user's movements using built-in sensors and provides feedback at the appropriate time.

[2450] Specific examples

[2451] For example, if a new employee needs to learn how to operate a new machine, the system works like this:

[2452] 1. A user (new employee) registers and logs in after completing email authentication.

[2453] 2. The user selects "Machine Operation" in their profile settings and enters their learning goals.

[2454] 3. Based on this information, the server generates a customized machine operation training program and displays it on the terminal.

[2455] 4. When a user enters a question during training, the server uses an AI chatbot to instantly generate an answer and display it on the device.

[2456] 5. The server schedules an online session with an expert, and the user joins the session and asks questions directly.

[2457] 6. Based on the user's progress data, the server generates a progress report and displays it to the user on the terminal.

[2458] 7. User reviews report and plans next learning steps.

[2459] 8. The robot guides the user through the work steps, uses sensors to detect movements and provides appropriate feedback.

[2460] Prompt Sentence Examples

[2461] "Please provide a method for designing an easy-to-use AI interactive robot trainer so that new employees can receive real-time answers to any questions they may have during training on new machine operation."

[2462] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2463] Step 1:

[2464] The user enters their profile information and learning goals, including their name, email address, password, interests, learning goals, etc. The device then sends this information to the server.

[2465] Step 2:

[2466] The server records the information in a user database based on the received user information, generates an email containing an authentication link, and sends it to the user. This allows the server to securely manage the user's profile information and start the authentication process.

[2467] Step 3:

[2468] When the user clicks on the link in the authentication email, the server activates the account, which causes the server to update the user's authentication status and grant access to the learning platform.

[2469] Step 4:

[2470] After logging in, users enter their interests and learning goals on the profile settings page. The device then sends this information back to the server, which then obtains the data needed to generate the most appropriate learning curriculum.

[2471] Step 5:

[2472] Based on the received information, the server uses an AI model to generate an individually customized learning curriculum, which includes learning content that reflects the user's interests and learning goals, and then sends the curriculum to the device and displays it to the user.

[2473] Step 6:

[2474] When a user enters a question or concern that arises during their study into their device, the question is sent to the server, which uses an AI chatbot to instantly generate an answer and send it to the device in real time, allowing users to immediately resolve any doubts they may have while studying.

[2475] Step 7:

[2476] The server periodically receives the user's learning progress data (e.g., completed assignments, test results, and study time). It analyzes the received data and generates a progress report. The generated progress report is sent to the terminal and displayed to the user.

[2477] Step 8:

[2478] The server schedules online sessions with experts or instructors as needed based on the user's learning progress, and the device displays a notification of the online session to the user and provides a session link at the specified time.

[2479] Step 9:

[2480] Once users click on the session link, an online session will begin, allowing for real-time interaction with experts and mentors, allowing users to directly ask questions about specific questions and issues and receive expert answers.

[2481] Step 10:

[2482] The AI-embedded robot guides users through work procedures and uses sensors to detect their movements. When users operate the equipment, the robot provides timely feedback, allowing users to receive effective training in a real-world work environment.

[2483] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[2484] This invention relates to an educational platform that utilizes an AI conversational chatbot and emotion recognition engine, and describes how to specifically implement the system to provide a personalized learning experience.

[2485] System configuration

[2486] This system consists of four components: the user, the device, the server, and the emotion engine, which work together to realize education. It also integrates AI chatbots with support from experts and teachers.

[2487] User Registration and Authentication

[2488] 1. A user accesses the educational platform's website or app and enters profile information such as name, email address, and password on the new registration screen.

[2489] 2. The device sends the entered profile information to the server.

[2490] 3. The server stores the user information in a database based on the received profile information.

[2491] 4. The server sends an email containing a verification link to the user's email address.

[2492] 5. The user clicks the link in the verification email to activate their account.

[2493] 6. The server verifies that the user clicked the link and updates the account status to "active."

[2494] Customized educational content

[2495] 1. The user logs in and accesses the profile settings page.

[2496] 2. The user inputs their area of ​​interest or learning goal (e.g., mathematics, high school level, specifically calculus).

[2497] 3. The device sends the user's input information to the server.

[2498] 4. Based on the information received by the server, the AI ​​chatbot algorithm is run to generate a customized learning curriculum.

[2499] 5. The server sends the generated curriculum to the terminal.

[2500] 6. The device displays t...

Claims

1. a means for users to input individual profile information and learning goals; A means for generating a learning curriculum based on the user information received by the server; means for transmitting the generated learning curriculum to a user's terminal and displaying it; A means for users to input questions that arise during learning, and for the server to instantly generate answers using AI; a means for the server to schedule online sessions with experts and teachers in real time; means for transmitting user learning progress data from the terminal to a server, and for the server to generate a progress report; A system including:

2. The server includes a means for generating recommended learning content at an appropriate time based on the user's learning progress and transmitting the content to the terminal. The system of claim 1 .

3. This includes using AI to analyze the questions entered by users and redirect them to experts. The system of claim 1 .

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